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|---|---|---|---|---|---|---|---|---|---|---|---|
The Devil Is in the Details: Delving Into Unbiased Data Processing for Human Pose Estimation
| 127
|
cvpr
| 49
| 10
|
2023-06-03 02:43:37.171000
|
https://github.com/HuangJunJie2017/UDP-Pose
| 287
|
The devil is in the details: Delving into unbiased data processing for human pose estimation
|
https://scholar.google.com/scholar?cluster=18010745089857323264&hl=en&as_sdt=0,5
| 10
| 2,020
|
SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition
| 172
|
cvpr
| 45
| 27
|
2023-06-03 02:43:37.372000
|
https://github.com/Pay20Y/SEED
| 163
|
Seed: Semantics enhanced encoder-decoder framework for scene text recognition
|
https://scholar.google.com/scholar?cluster=13345330189856644630&hl=en&as_sdt=0,47
| 11
| 2,020
|
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization
| 93
|
cvpr
| 8
| 0
|
2023-06-03 02:43:37.572000
|
https://github.com/Saehyung-Lee/cifar10_challenge
| 12
|
Adversarial vertex mixup: Toward better adversarially robust generalization
|
https://scholar.google.com/scholar?cluster=434632984174982270&hl=en&as_sdt=0,6
| 1
| 2,020
|
GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-Wise Transformations
| 39
|
cvpr
| 18
| 6
|
2023-06-03 02:43:37.774000
|
https://github.com/gyshgx868/graph-ter
| 56
|
Graphter: Unsupervised learning of graph transformation equivariant representations via auto-encoding node-wise transformations
|
https://scholar.google.com/scholar?cluster=1198484586266735161&hl=en&as_sdt=0,33
| 7
| 2,020
|
iTAML: An Incremental Task-Agnostic Meta-learning Approach
| 127
|
cvpr
| 14
| 5
|
2023-06-03 02:43:37.976000
|
https://github.com/brjathu/iTAML
| 91
|
itaml: An incremental task-agnostic meta-learning approach
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https://scholar.google.com/scholar?cluster=13903317510243634709&hl=en&as_sdt=0,50
| 3
| 2,020
|
Single Image Reflection Removal Through Cascaded Refinement
| 88
|
cvpr
| 17
| 7
|
2023-06-03 02:43:38.177000
|
https://github.com/JHL-HUST/IBCLN
| 103
|
Single image reflection removal through cascaded refinement
|
https://scholar.google.com/scholar?cluster=15885579593007132929&hl=en&as_sdt=0,21
| 8
| 2,020
|
GrappaNet: Combining Parallel Imaging With Deep Learning for Multi-Coil MRI Reconstruction
| 74
|
cvpr
| 345
| 12
|
2023-06-03 02:43:38.379000
|
https://github.com/facebookresearch/fastMRI
| 1,101
|
GrappaNet: Combining parallel imaging with deep learning for multi-coil MRI reconstruction
|
https://scholar.google.com/scholar?cluster=15085105229863616742&hl=en&as_sdt=0,5
| 77
| 2,020
|
Distilled Semantics for Comprehensive Scene Understanding from Videos
| 55
|
cvpr
| 12
| 5
|
2023-06-03 02:43:38.585000
|
https://github.com/CVLAB-Unibo/omeganet
| 57
|
Distilled semantics for comprehensive scene understanding from videos
|
https://scholar.google.com/scholar?cluster=12147029063592298350&hl=en&as_sdt=0,39
| 13
| 2,020
|
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions
| 246
|
cvpr
| 142
| 20
|
2023-06-03 02:43:38.786000
|
https://github.com/facebookresearch/mobile-vision
| 852
|
Fbnetv2: Differentiable neural architecture search for spatial and channel dimensions
|
https://scholar.google.com/scholar?cluster=14734050071484694995&hl=en&as_sdt=0,33
| 46
| 2,020
|
VOLDOR: Visual Odometry From Log-Logistic Dense Optical Flow Residuals
| 33
|
cvpr
| 48
| 3
|
2023-06-03 02:43:38.987000
|
https://github.com/htkseason/VOLDOR
| 364
|
Voldor: Visual odometry from log-logistic dense optical flow residuals
|
https://scholar.google.com/scholar?cluster=1784635091325992885&hl=en&as_sdt=0,5
| 17
| 2,020
|
P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds
| 96
|
cvpr
| 33
| 17
|
2023-06-03 02:43:39.188000
|
https://github.com/HaozheQi/P2B
| 175
|
P2b: Point-to-box network for 3d object tracking in point clouds
|
https://scholar.google.com/scholar?cluster=735697306593238715&hl=en&as_sdt=0,38
| 7
| 2,020
|
Scale-Equalizing Pyramid Convolution for Object Detection
| 90
|
cvpr
| 56
| 4
|
2023-06-03 02:43:39.388000
|
https://github.com/jshilong/SEPC
| 326
|
Scale-equalizing pyramid convolution for object detection
|
https://scholar.google.com/scholar?cluster=443944663207581625&hl=en&as_sdt=0,5
| 13
| 2,020
|
Learning Selective Self-Mutual Attention for RGB-D Saliency Detection
| 204
|
cvpr
| 8
| 6
|
2023-06-03 02:43:39.590000
|
https://github.com/nnizhang/S2MA
| 60
|
Learning selective self-mutual attention for RGB-D saliency detection
|
https://scholar.google.com/scholar?cluster=14128598538897215193&hl=en&as_sdt=0,21
| 3
| 2,020
|
Learning to Transfer Texture From Clothing Images to 3D Humans
| 80
|
cvpr
| 57
| 37
|
2023-06-03 02:43:39.791000
|
https://github.com/aymenmir1/pix2surf
| 294
|
Learning to transfer texture from clothing images to 3d humans
|
https://scholar.google.com/scholar?cluster=12771096843818017968&hl=en&as_sdt=0,5
| 5
| 2,020
|
Semi-Supervised Learning for Few-Shot Image-to-Image Translation
| 40
|
cvpr
| 5
| 2
|
2023-06-03 02:43:39.991000
|
https://github.com/yaxingwang/SEMIT
| 49
|
Semi-supervised learning for few-shot image-to-image translation
|
https://scholar.google.com/scholar?cluster=2129382269487229002&hl=en&as_sdt=0,5
| 10
| 2,020
|
Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning
| 189
|
cvpr
| 87
| 14
|
2023-06-03 02:43:40.193000
|
https://github.com/microsoft/DisentangledFaceGAN
| 570
|
Disentangled and controllable face image generation via 3d imitative-contrastive learning
|
https://scholar.google.com/scholar?cluster=15496471340661576046&hl=en&as_sdt=0,5
| 37
| 2,020
|
DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learning
| 42
|
cvpr
| 2
| 1
|
2023-06-03 02:43:40.393000
|
https://github.com/jspenmar/DeFeat-Net
| 23
|
Defeat-net: General monocular depth via simultaneous unsupervised representation learning
|
https://scholar.google.com/scholar?cluster=10482583096470600686&hl=en&as_sdt=0,44
| 2
| 2,020
|
Multi-Scale Interactive Network for Salient Object Detection
| 445
|
cvpr
| 28
| 2
|
2023-06-03 02:43:40.593000
|
https://github.com/lartpang/MINet
| 223
|
Multi-scale interactive network for salient object detection
|
https://scholar.google.com/scholar?cluster=1179192240058937367&hl=en&as_sdt=0,10
| 10
| 2,020
|
Regularizing Class-Wise Predictions via Self-Knowledge Distillation
| 198
|
cvpr
| 22
| 4
|
2023-06-03 02:43:40.794000
|
https://github.com/alinlab/cs-kd
| 93
|
Regularizing class-wise predictions via self-knowledge distillation
|
https://scholar.google.com/scholar?cluster=11350076008765834853&hl=en&as_sdt=0,5
| 6
| 2,020
|
Universal Source-Free Domain Adaptation
| 206
|
cvpr
| 0
| 0
|
2023-06-03 02:43:40.995000
|
https://github.com/val-iisc/usfda
| 14
|
Universal source-free domain adaptation
|
https://scholar.google.com/scholar?cluster=13396021133130094693&hl=en&as_sdt=0,33
| 12
| 2,020
|
Meta-Transfer Learning for Zero-Shot Super-Resolution
| 235
|
cvpr
| 59
| 29
|
2023-06-03 02:43:41.195000
|
https://github.com/JWSoh/MZSR
| 254
|
Meta-transfer learning for zero-shot super-resolution
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https://scholar.google.com/scholar?cluster=4901353720515503142&hl=en&as_sdt=0,5
| 4
| 2,020
|
A Model-Driven Deep Neural Network for Single Image Rain Removal
| 210
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cvpr
| 21
| 8
|
2023-06-03 02:43:41.397000
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https://github.com/hongwang01/RCDNet
| 156
|
A model-driven deep neural network for single image rain removal
|
https://scholar.google.com/scholar?cluster=11451290027329888829&hl=en&as_sdt=0,41
| 7
| 2,020
|
Learning to Manipulate Individual Objects in an Image
| 32
|
cvpr
| 0
| 0
|
2023-06-03 02:43:41.598000
|
https://github.com/ChenYutongTHU/Learning-to-manipulate-individual-objects-in-an-image-Implementation
| 12
|
Learning to manipulate individual objects in an image
|
https://scholar.google.com/scholar?cluster=8469380198303178771&hl=en&as_sdt=0,33
| 4
| 2,020
|
High-Dimensional Convolutional Networks for Geometric Pattern Recognition
| 32
|
cvpr
| 4
| 1
|
2023-06-03 02:43:41.799000
|
https://github.com/chrischoy/HighDimConvNets
| 34
|
High-dimensional convolutional networks for geometric pattern recognition
|
https://scholar.google.com/scholar?cluster=4842349631480755356&hl=en&as_sdt=0,5
| 14
| 2,020
|
3D Photography Using Context-Aware Layered Depth Inpainting
| 185
|
cvpr
| 1,097
| 98
|
2023-06-03 02:43:42
|
https://github.com/vt-vl-lab/3d-photo-inpainting
| 6,511
|
3d photography using context-aware layered depth inpainting
|
https://scholar.google.com/scholar?cluster=13896011424140202640&hl=en&as_sdt=0,10
| 147
| 2,020
|
AOWS: Adaptive and Optimal Network Width Search With Latency Constraints
| 31
|
cvpr
| 4
| 0
|
2023-06-03 02:43:42.201000
|
https://github.com/bermanmaxim/AOWS
| 34
|
Aows: Adaptive and optimal network width search with latency constraints
|
https://scholar.google.com/scholar?cluster=10309035712406235754&hl=en&as_sdt=0,5
| 5
| 2,020
|
APQ: Joint Search for Network Architecture, Pruning and Quantization Policy
| 150
|
cvpr
| 33
| 6
|
2023-06-03 02:43:42.401000
|
https://github.com/mit-han-lab/apq
| 141
|
Apq: Joint search for network architecture, pruning and quantization policy
|
https://scholar.google.com/scholar?cluster=1374069721944449122&hl=en&as_sdt=0,14
| 11
| 2,020
|
Grid-GCN for Fast and Scalable Point Cloud Learning
| 190
|
cvpr
| 24
| 10
|
2023-06-03 02:43:42.602000
|
https://github.com/Xharlie/Grid-GCN
| 177
|
Grid-gcn for fast and scalable point cloud learning
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https://scholar.google.com/scholar?cluster=531285662278739329&hl=en&as_sdt=0,5
| 11
| 2,020
|
Attentive Weights Generation for Few Shot Learning via Information Maximization
| 88
|
cvpr
| 1
| 1
|
2023-06-03 02:43:42.803000
|
https://github.com/Yiluan/AWGIM
| 15
|
Attentive weights generation for few shot learning via information maximization
|
https://scholar.google.com/scholar?cluster=9022059591117885883&hl=en&as_sdt=0,48
| 2
| 2,020
|
KFNet: Learning Temporal Camera Relocalization Using Kalman Filtering
| 51
|
cvpr
| 28
| 3
|
2023-06-03 02:43:43.004000
|
https://github.com/zlthinker/KFNet
| 204
|
Kfnet: Learning temporal camera relocalization using kalman filtering
|
https://scholar.google.com/scholar?cluster=653147639240971150&hl=en&as_sdt=0,5
| 8
| 2,020
|
Semantic Correspondence as an Optimal Transport Problem
| 90
|
cvpr
| 10
| 4
|
2023-06-03 02:43:43.204000
|
https://github.com/csyanbin/SCOT
| 95
|
Semantic correspondence as an optimal transport problem
|
https://scholar.google.com/scholar?cluster=200912752079271114&hl=en&as_sdt=0,47
| 1
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SuperGlue: Learning Feature Matching With Graph Neural Networks
| 1,068
|
cvpr
| 547
| 40
|
2023-06-03 02:43:43.405000
|
https://github.com/magicleap/SuperGluePretrainedNetwork
| 2,486
|
Superglue: Learning feature matching with graph neural networks
|
https://scholar.google.com/scholar?cluster=15521088276096645515&hl=en&as_sdt=0,5
| 58
| 2,020
|
Improving Confidence Estimates for Unfamiliar Examples
| 35
|
cvpr
| 1
| 0
|
2023-06-03 02:43:43.606000
|
https://github.com/lizhitwo/ConfidenceEstimates
| 11
|
Improving confidence estimates for unfamiliar examples
|
https://scholar.google.com/scholar?cluster=12998595608002202111&hl=en&as_sdt=0,39
| 2
| 2,020
|
How Useful Is Self-Supervised Pretraining for Visual Tasks?
| 91
|
cvpr
| 3
| 1
|
2023-06-03 02:43:43.806000
|
https://github.com/princeton-vl/selfstudy
| 59
|
How useful is self-supervised pretraining for visual tasks?
|
https://scholar.google.com/scholar?cluster=464561574781045149&hl=en&as_sdt=0,10
| 10
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|
Learning to Segment the Tail
| 62
|
cvpr
| 6
| 1
|
2023-06-03 02:43:44.006000
|
https://github.com/JoyHuYY1412/LST_LVIS
| 46
|
Learning to segment the tail
|
https://scholar.google.com/scholar?cluster=14793983145216247407&hl=en&as_sdt=0,5
| 3
| 2,020
|
Action Segmentation With Joint Self-Supervised Temporal Domain Adaptation
| 91
|
cvpr
| 22
| 0
|
2023-06-03 02:43:44.207000
|
https://github.com/cmhungsteve/SSTDA
| 151
|
Action segmentation with joint self-supervised temporal domain adaptation
|
https://scholar.google.com/scholar?cluster=1572542229157505218&hl=en&as_sdt=0,5
| 10
| 2,020
|
ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
| 385
|
cvpr
| 66
| 17
|
2023-06-03 02:43:44.408000
|
https://github.com/askforalfred/alfred
| 241
|
Alfred: A benchmark for interpreting grounded instructions for everyday tasks
|
https://scholar.google.com/scholar?cluster=10541831682119160249&hl=en&as_sdt=0,36
| 16
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|
MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices
| 49
|
cvpr
| 46,274
| 1,204
|
2023-06-03 02:43:44.608000
|
https://github.com/tensorflow/models
| 75,883
|
Mnasfpn: Learning latency-aware pyramid architecture for object detection on mobile devices
|
https://scholar.google.com/scholar?cluster=15212100434147300168&hl=en&as_sdt=0,10
| 2,774
| 2,020
|
Syn2Real Transfer Learning for Image Deraining Using Gaussian Processes
| 140
|
cvpr
| 39
| 2
|
2023-06-03 02:43:44.815000
|
https://github.com/rajeevyasarla/Syn2Real
| 130
|
Syn2real transfer learning for image deraining using gaussian processes
|
https://scholar.google.com/scholar?cluster=13979737242954461405&hl=en&as_sdt=0,5
| 3
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|
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression
| 164
|
cvpr
| 13
| 4
|
2023-06-03 02:43:45.016000
|
https://github.com/ofsoundof/group_sparsity
| 55
|
Group sparsity: The hinge between filter pruning and decomposition for network compression
|
https://scholar.google.com/scholar?cluster=185943989367242161&hl=en&as_sdt=0,33
| 5
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|
On Isometry Robustness of Deep 3D Point Cloud Models Under Adversarial Attacks
| 48
|
cvpr
| 12
| 7
|
2023-06-03 02:43:45.217000
|
https://github.com/skywalker6174/3d-isometry-robust
| 22
|
On isometry robustness of deep 3d point cloud models under adversarial attacks
|
https://scholar.google.com/scholar?cluster=17634312630840810623&hl=en&as_sdt=0,33
| 3
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|
P-nets: Deep Polynomial Neural Networks
| 51
|
cvpr
| 31
| 5
|
2023-06-03 02:43:45.418000
|
https://github.com/grigorisg9gr/polynomial_nets
| 144
|
P-nets: Deep polynomial neural networks
|
https://scholar.google.com/scholar?cluster=10054840496985054567&hl=en&as_sdt=0,26
| 6
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|
Straight to the Point: Fast-Forwarding Videos via Reinforcement Learning Using Textual Data
| 6
|
cvpr
| 1
| 0
|
2023-06-03 02:43:45.619000
|
https://github.com/verlab/StraightToThePoint_CVPR_2020
| 8
|
Straight to the point: Fast-forwarding videos via reinforcement learning using textual data
|
https://scholar.google.com/scholar?cluster=4421532250936590050&hl=en&as_sdt=0,33
| 4
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|
Self-Supervised Viewpoint Learning From Image Collections
| 37
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cvpr
| 28
| 2
|
2023-06-03 02:43:45.820000
|
https://github.com/NVlabs/SSV
| 215
|
Self-supervised viewpoint learning from image collections
|
https://scholar.google.com/scholar?cluster=546931561469949809&hl=en&as_sdt=0,8
| 22
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|
G3AN: Disentangling Appearance and Motion for Video Generation
| 59
|
cvpr
| 8
| 4
|
2023-06-03 02:43:46.020000
|
https://github.com/wyhsirius/g3an-project
| 36
|
G3AN: Disentangling appearance and motion for video generation
|
https://scholar.google.com/scholar?cluster=1852334605769980573&hl=en&as_sdt=0,33
| 6
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|
SPARE3D: A Dataset for SPAtial REasoning on Three-View Line Drawings
| 10
|
cvpr
| 8
| 1
|
2023-06-03 02:43:46.222000
|
https://github.com/ai4ce/SPARE3D
| 48
|
Spare3d: A dataset for spatial reasoning on three-view line drawings
|
https://scholar.google.com/scholar?cluster=6953548346558587780&hl=en&as_sdt=0,5
| 7
| 2,020
|
On the Uncertainty of Self-Supervised Monocular Depth Estimation
| 152
|
cvpr
| 24
| 7
|
2023-06-03 02:43:46.423000
|
https://github.com/mattpoggi/mono-uncertainty
| 215
|
On the uncertainty of self-supervised monocular depth estimation
|
https://scholar.google.com/scholar?cluster=17564970690624367035&hl=en&as_sdt=0,5
| 8
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|
DeepFaceFlow: In-the-Wild Dense 3D Facial Motion Estimation
| 8
|
cvpr
| 4
| 3
|
2023-06-03 02:43:46.623000
|
https://github.com/mrkoujan/DeepFaceFlow
| 80
|
DeepFaceFlow: in-the-wild dense 3D facial motion estimation
|
https://scholar.google.com/scholar?cluster=2315487414431800146&hl=en&as_sdt=0,5
| 21
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|
StegaStamp: Invisible Hyperlinks in Physical Photographs
| 166
|
cvpr
| 164
| 25
|
2023-06-03 02:43:46.824000
|
https://github.com/tancik/StegaStamp
| 556
|
Stegastamp: Invisible hyperlinks in physical photographs
|
https://scholar.google.com/scholar?cluster=9141986600005221060&hl=en&as_sdt=0,33
| 15
| 2,020
|
TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model
| 202
|
cvpr
| 22
| 9
|
2023-06-03 02:43:47.025000
|
https://github.com/BoPang1996/TubeTK
| 138
|
Tubetk: Adopting tubes to track multi-object in a one-step training model
|
https://scholar.google.com/scholar?cluster=9897780157833606863&hl=en&as_sdt=0,10
| 9
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|
Instance-Aware, Context-Focused, and Memory-Efficient Weakly Supervised Object Detection
| 160
|
cvpr
| 45
| 10
|
2023-06-03 02:43:47.226000
|
https://github.com/NVlabs/wetectron
| 348
|
Instance-aware, context-focused, and memory-efficient weakly supervised object detection
|
https://scholar.google.com/scholar?cluster=13727446774856898528&hl=en&as_sdt=0,33
| 31
| 2,020
|
Anisotropic Convolutional Networks for 3D Semantic Scene Completion
| 37
|
cvpr
| 14
| 5
|
2023-06-03 02:43:47.427000
|
https://github.com/waterljwant/SSC
| 81
|
Anisotropic convolutional networks for 3d semantic scene completion
|
https://scholar.google.com/scholar?cluster=12549089821990650739&hl=en&as_sdt=0,23
| 5
| 2,020
|
Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation
| 175
|
cvpr
| 13
| 7
|
2023-06-03 02:43:47.628000
|
https://github.com/SHI-Labs/Unsupervised-Domain-Adaptation-with-Differential-Treatment
| 81
|
Differential treatment for stuff and things: A simple unsupervised domain adaptation method for semantic segmentation
|
https://scholar.google.com/scholar?cluster=15596513768387323912&hl=en&as_sdt=0,5
| 8
| 2,020
|
Cascaded Refinement Network for Point Cloud Completion
| 178
|
cvpr
| 2
| 1
|
2023-06-03 02:43:47.829000
|
https://github.com/xiaogangw/cascaded-point-completion
| 18
|
Cascaded refinement network for point cloud completion
|
https://scholar.google.com/scholar?cluster=15354810067135987183&hl=en&as_sdt=0,5
| 1
| 2,020
|
Video Object Grounding Using Semantic Roles in Language Description
| 36
|
cvpr
| 7
| 1
|
2023-06-03 02:43:48.029000
|
https://github.com/TheShadow29/vognet-pytorch
| 67
|
Video object grounding using semantic roles in language description
|
https://scholar.google.com/scholar?cluster=11262259591850878257&hl=en&as_sdt=0,5
| 4
| 2,020
|
Rotation Equivariant Graph Convolutional Network for Spherical Image Classification
| 28
|
cvpr
| 0
| 1
|
2023-06-03 02:43:48.230000
|
https://github.com/QinYang12/SGCN
| 14
|
Rotation equivariant graph convolutional network for spherical image classification
|
https://scholar.google.com/scholar?cluster=6340965602733917547&hl=en&as_sdt=0,5
| 6
| 2,020
|
MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks
| 178
|
cvpr
| 59
| 3
|
2023-06-03 02:43:48.431000
|
https://github.com/akanimax/msg-stylegan-tf
| 258
|
Msg-gan: Multi-scale gradients for generative adversarial networks
|
https://scholar.google.com/scholar?cluster=17634072045755762910&hl=en&as_sdt=0,44
| 14
| 2,020
|
DIST: Rendering Deep Implicit Signed Distance Function With Differentiable Sphere Tracing
| 209
|
cvpr
| 26
| 5
|
2023-06-03 02:43:48.632000
|
https://github.com/B1ueber2y/DIST-Renderer
| 209
|
Dist: Rendering deep implicit signed distance function with differentiable sphere tracing
|
https://scholar.google.com/scholar?cluster=1091979672567186905&hl=en&as_sdt=0,5
| 12
| 2,020
|
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation
| 94
|
cvpr
| 34
| 5
|
2023-06-03 02:43:48.833000
|
https://github.com/zju3dv/disprcnn
| 202
|
Disp r-cnn: Stereo 3d object detection via shape prior guided instance disparity estimation
|
https://scholar.google.com/scholar?cluster=9023656501136172103&hl=en&as_sdt=0,5
| 12
| 2,020
|
Interactive Two-Stream Decoder for Accurate and Fast Saliency Detection
| 247
|
cvpr
| 10
| 9
|
2023-06-03 02:43:49.033000
|
https://github.com/moothes/ITSD-pytorch
| 67
|
Interactive two-stream decoder for accurate and fast saliency detection
|
https://scholar.google.com/scholar?cluster=2698893050538436365&hl=en&as_sdt=0,5
| 4
| 2,020
|
Episode-Based Prototype Generating Network for Zero-Shot Learning
| 128
|
cvpr
| 6
| 4
|
2023-06-03 02:43:49.235000
|
https://github.com/yunlongyu/EPGN
| 24
|
Episode-based prototype generating network for zero-shot learning
|
https://scholar.google.com/scholar?cluster=15377338687069834231&hl=en&as_sdt=0,31
| 2
| 2,020
|
ViewAL: Active Learning With Viewpoint Entropy for Semantic Segmentation
| 109
|
cvpr
| 25
| 4
|
2023-06-03 02:43:49.436000
|
https://github.com/nihalsid/ViewAL
| 132
|
Viewal: Active learning with viewpoint entropy for semantic segmentation
|
https://scholar.google.com/scholar?cluster=13436330028069882717&hl=en&as_sdt=0,44
| 8
| 2,020
|
A U-Net Based Discriminator for Generative Adversarial Networks
| 215
|
cvpr
| 53
| 8
|
2023-06-03 02:43:49.637000
|
https://github.com/boschresearch/unetgan
| 326
|
A u-net based discriminator for generative adversarial networks
|
https://scholar.google.com/scholar?cluster=6120539919740151426&hl=en&as_sdt=0,37
| 8
| 2,020
|
Semi-Supervised Semantic Segmentation With Cross-Consistency Training
| 414
|
cvpr
| 54
| 1
|
2023-06-03 02:43:49.838000
|
https://github.com/yassouali/CCT
| 357
|
Semi-supervised semantic segmentation with cross-consistency training
|
https://scholar.google.com/scholar?cluster=16388515887267992352&hl=en&as_sdt=0,5
| 10
| 2,020
|
Diversified Arbitrary Style Transfer via Deep Feature Perturbation
| 74
|
cvpr
| 8
| 0
|
2023-06-03 02:43:50.039000
|
https://github.com/EndyWon/Deep-Feature-Perturbation
| 35
|
Diversified arbitrary style transfer via deep feature perturbation
|
https://scholar.google.com/scholar?cluster=7181013307985111414&hl=en&as_sdt=0,5
| 5
| 2,020
|
GaitPart: Temporal Part-Based Model for Gait Recognition
| 211
|
cvpr
| 106
| 9
|
2023-06-03 02:43:50.240000
|
https://github.com/shiqiyu/opengait
| 422
|
Gaitpart: Temporal part-based model for gait recognition
|
https://scholar.google.com/scholar?cluster=16505851961146284687&hl=en&as_sdt=0,5
| 14
| 2,020
|
Adversarial Examples Improve Image Recognition
| 417
|
cvpr
| 1,788
| 293
|
2023-06-03 02:43:50.441000
|
https://github.com/tensorflow/tpu
| 5,123
|
Adversarial examples improve image recognition
|
https://scholar.google.com/scholar?cluster=12540097159832752079&hl=en&as_sdt=0,5
| 371
| 2,020
|
Defending and Harnessing the Bit-Flip Based Adversarial Weight Attack
| 57
|
cvpr
| 9
| 0
|
2023-06-03 02:43:50.641000
|
https://github.com/elliothe/BFA
| 27
|
Defending and harnessing the bit-flip based adversarial weight attack
|
https://scholar.google.com/scholar?cluster=4166950612750375922&hl=en&as_sdt=0,39
| 2
| 2,020
|
TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution
| 405
|
cvpr
| 63
| 19
|
2023-06-03 02:43:50.842000
|
https://github.com/YapengTian/TDAN-VSR-CVPR-2020
| 388
|
Tdan: Temporally-deformable alignment network for video super-resolution
|
https://scholar.google.com/scholar?cluster=9134144164731399402&hl=en&as_sdt=0,5
| 12
| 2,020
|
LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood
| 121
|
cvpr
| 2
| 1
|
2023-06-03 02:43:51.043000
|
https://github.com/abhi1kumar/LUVLi
| 27
|
Luvli face alignment: Estimating landmarks' location, uncertainty, and visibility likelihood
|
https://scholar.google.com/scholar?cluster=10496106229213355393&hl=en&as_sdt=0,50
| 3
| 2,020
|
Resolution Adaptive Networks for Efficient Inference
| 128
|
cvpr
| 28
| 0
|
2023-06-03 02:43:51.245000
|
https://github.com/yangle15/RANet-pytorch
| 139
|
Resolution adaptive networks for efficient inference
|
https://scholar.google.com/scholar?cluster=521101430028285536&hl=en&as_sdt=0,33
| 5
| 2,020
|
PointAugment: An Auto-Augmentation Framework for Point Cloud Classification
| 107
|
cvpr
| 27
| 9
|
2023-06-03 02:43:51.445000
|
https://github.com/liruihui/PointAugment
| 188
|
Pointaugment: an auto-augmentation framework for point cloud classification
|
https://scholar.google.com/scholar?cluster=14167102715363724840&hl=en&as_sdt=0,5
| 15
| 2,020
|
Normal Assisted Stereo Depth Estimation
| 57
|
cvpr
| 20
| 7
|
2023-06-03 02:43:51.646000
|
https://github.com/udaykusupati/Normal-Assisted-Stereo
| 98
|
Normal assisted stereo depth estimation
|
https://scholar.google.com/scholar?cluster=1339319511524156641&hl=en&as_sdt=0,11
| 5
| 2,020
|
Siamese Box Adaptive Network for Visual Tracking
| 550
|
cvpr
| 48
| 30
|
2023-06-03 02:43:51.847000
|
https://github.com/hqucv/siamban
| 243
|
Siamese box adaptive network for visual tracking
|
https://scholar.google.com/scholar?cluster=9040151999224305592&hl=en&as_sdt=0,5
| 7
| 2,020
|
EfficientDet: Scalable and Efficient Object Detection
| 3,680
|
cvpr
| 1,452
| 146
|
2023-06-03 02:43:52.048000
|
https://github.com/google/automl
| 5,884
|
Efficientdet: Scalable and efficient object detection
|
https://scholar.google.com/scholar?cluster=16138254679061222132&hl=en&as_sdt=0,39
| 158
| 2,020
|
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF From a Single Image
| 139
|
cvpr
| 32
| 8
|
2023-06-03 02:43:52.249000
|
https://github.com/lzqsd/InverseRenderingOfIndoorScene
| 236
|
Inverse rendering for complex indoor scenes: Shape, spatially-varying lighting and svbrdf from a single image
|
https://scholar.google.com/scholar?cluster=15619834795097106737&hl=en&as_sdt=0,19
| 14
| 2,020
|
Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer
| 80
|
cvpr
| 15
| 0
|
2023-06-03 02:43:52.451000
|
https://github.com/UCMerced-ML/LC-model-compression
| 47
|
Low-rank compression of neural nets: Learning the rank of each layer
|
https://scholar.google.com/scholar?cluster=11332208454238811935&hl=en&as_sdt=0,31
| 6
| 2,020
|
Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS
| 115
|
cvpr
| 7,284
| 1,013
|
2023-06-03 02:43:52.651000
|
https://github.com/google-research/google-research
| 29,540
|
Can weight sharing outperform random architecture search? an investigation with tunas
|
https://scholar.google.com/scholar?cluster=10742561815901242531&hl=en&as_sdt=0,5
| 727
| 2,020
|
There and Back Again: Revisiting Backpropagation Saliency Methods
| 101
|
cvpr
| 3
| 0
|
2023-06-03 02:43:52.852000
|
https://github.com/srebuffi/revisiting_saliency
| 49
|
There and back again: Revisiting backpropagation saliency methods
|
https://scholar.google.com/scholar?cluster=5600358576607487078&hl=en&as_sdt=0,10
| 4
| 2,020
|
RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network
| 187
|
cvpr
| 679
| 61
|
2023-06-03 02:43:53.053000
|
https://github.com/facebookarchive/fb.resnet.torch
| 2,210
|
Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network
|
https://scholar.google.com/scholar?cluster=10751549547661791339&hl=en&as_sdt=0,33
| 121
| 2,020
|
Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-Weighting
| 62
|
cvpr
| 4
| 1
|
2023-06-03 02:43:53.254000
|
https://github.com/dliu5812/PDAM
| 15
|
Unsupervised instance segmentation in microscopy images via panoptic domain adaptation and task re-weighting
|
https://scholar.google.com/scholar?cluster=4954223067594419011&hl=en&as_sdt=0,41
| 2
| 2,020
|
Learning Meta Face Recognition in Unseen Domains
| 121
|
cvpr
| 18
| 4
|
2023-06-03 02:43:53.454000
|
https://github.com/cleardusk/MFR
| 147
|
Learning meta face recognition in unseen domains
|
https://scholar.google.com/scholar?cluster=4359786759676260995&hl=en&as_sdt=0,14
| 20
| 2,020
|
Heterogeneous Knowledge Distillation Using Information Flow Modeling
| 92
|
cvpr
| 6
| 0
|
2023-06-03 02:43:53.655000
|
https://github.com/passalis/pkth
| 22
|
Heterogeneous knowledge distillation using information flow modeling
|
https://scholar.google.com/scholar?cluster=10960912660981244645&hl=en&as_sdt=0,5
| 2
| 2,020
|
An Adaptive Neural Network for Unsupervised Mosaic Consistency Analysis in Image Forensics
| 25
|
cvpr
| 3
| 2
|
2023-06-03 02:43:53.856000
|
https://github.com/qbammey/adaptive_cfa_forensics
| 25
|
An adaptive neural network for unsupervised mosaic consistency analysis in image forensics
|
https://scholar.google.com/scholar?cluster=123983947089796389&hl=en&as_sdt=0,24
| 1
| 2,020
|
CARS: Continuous Evolution for Efficient Neural Architecture Search
| 194
|
cvpr
| 20
| 4
|
2023-06-03 02:43:54.057000
|
https://github.com/huawei-noah/CARS
| 102
|
Cars: Continuous evolution for efficient neural architecture search
|
https://scholar.google.com/scholar?cluster=10174262153417334156&hl=en&as_sdt=0,5
| 10
| 2,020
|
State-Aware Tracker for Real-Time Video Object Segmentation
| 81
|
cvpr
| 178
| 19
|
2023-06-03 02:43:54.258000
|
https://github.com/MegviiDetection/video_analyst
| 778
|
State-aware tracker for real-time video object segmentation
|
https://scholar.google.com/scholar?cluster=2093076341053017829&hl=en&as_sdt=0,48
| 30
| 2,020
|
Sign Language Transformers: Joint End-to-End Sign Language Recognition and Translation
| 309
|
cvpr
| 79
| 10
|
2023-06-03 02:43:54.458000
|
https://github.com/neccam/slt
| 178
|
Sign language transformers: Joint end-to-end sign language recognition and translation
|
https://scholar.google.com/scholar?cluster=3781725358102616609&hl=en&as_sdt=0,31
| 12
| 2,020
|
DualSDF: Semantic Shape Manipulation Using a Two-Level Representation
| 82
|
cvpr
| 18
| 3
|
2023-06-03 02:43:54.660000
|
https://github.com/zekunhao1995/DualSDF
| 126
|
Dualsdf: Semantic shape manipulation using a two-level representation
|
https://scholar.google.com/scholar?cluster=8918146941403724904&hl=en&as_sdt=0,6
| 13
| 2,020
|
A Context-Aware Loss Function for Action Spotting in Soccer Videos
| 64
|
cvpr
| 7
| 0
|
2023-06-03 02:43:54.860000
|
https://github.com/cioppaanthony/context-aware-loss
| 26
|
A context-aware loss function for action spotting in soccer videos
|
https://scholar.google.com/scholar?cluster=7407375010675176273&hl=en&as_sdt=0,5
| 5
| 2,020
|
The Edge of Depth: Explicit Constraints Between Segmentation and Depth
| 83
|
cvpr
| 11
| 11
|
2023-06-03 02:43:55.061000
|
https://github.com/TWJianNuo/EdgeDepth-Release
| 88
|
The edge of depth: Explicit constraints between segmentation and depth
|
https://scholar.google.com/scholar?cluster=6230826594737072707&hl=en&as_sdt=0,22
| 6
| 2,020
|
ReSprop: Reuse Sparsified Backpropagation
| 12
|
cvpr
| 1
| 1
|
2023-06-03 02:43:55.263000
|
https://github.com/negargoli/ReSprop
| 13
|
Resprop: Reuse sparsified backpropagation
|
https://scholar.google.com/scholar?cluster=15598805521506665571&hl=en&as_sdt=0,5
| 3
| 2,020
|
Deep Face Super-Resolution With Iterative Collaboration Between Attentive Recovery and Landmark Estimation
| 113
|
cvpr
| 62
| 9
|
2023-06-03 02:43:55.463000
|
https://github.com/Maclory/Deep-Iterative-Collaboration
| 286
|
Deep face super-resolution with iterative collaboration between attentive recovery and landmark estimation
|
https://scholar.google.com/scholar?cluster=14954402977731707377&hl=en&as_sdt=0,36
| 14
| 2,020
|
Learning a Unified Sample Weighting Network for Object Detection
| 35
|
cvpr
| 13
| 1
|
2023-06-03 02:43:55.665000
|
https://github.com/caiqi/sample-weighting-network
| 87
|
Learning a unified sample weighting network for object detection
|
https://scholar.google.com/scholar?cluster=6164165735538464051&hl=en&as_sdt=0,10
| 4
| 2,020
|
Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper Network
| 238
|
cvpr
| 43
| 31
|
2023-06-03 02:43:55.866000
|
https://github.com/SSL92/hyperIQA
| 272
|
Blindly assess image quality in the wild guided by a self-adaptive hyper network
|
https://scholar.google.com/scholar?cluster=81969699158088231&hl=en&as_sdt=0,44
| 8
| 2,020
|
Bundle Adjustment on a Graph Processor
| 35
|
cvpr
| 12
| 1
|
2023-06-03 02:43:56.067000
|
https://github.com/joeaortiz/gbp
| 66
|
Bundle adjustment on a graph processor
|
https://scholar.google.com/scholar?cluster=10217492741597882999&hl=en&as_sdt=0,5
| 5
| 2,020
|
Multi-View Neural Human Rendering
| 68
|
cvpr
| 9
| 3
|
2023-06-03 02:43:56.275000
|
https://github.com/wuminye/NHR
| 85
|
Multi-view neural human rendering
|
https://scholar.google.com/scholar?cluster=10314501776894360592&hl=en&as_sdt=0,34
| 8
| 2,020
|
Learning Fast and Robust Target Models for Video Object Segmentation
| 105
|
cvpr
| 25
| 7
|
2023-06-03 02:43:56.477000
|
https://github.com/andr345/frtm-vos
| 119
|
Learning fast and robust target models for video object segmentation
|
https://scholar.google.com/scholar?cluster=11207612305703571917&hl=en&as_sdt=0,5
| 9
| 2,020
|
Adaptive Loss-Aware Quantization for Multi-Bit Networks
| 34
|
cvpr
| 6
| 0
|
2023-06-03 02:43:56.678000
|
https://github.com/zqu1992/ALQ
| 12
|
Adaptive loss-aware quantization for multi-bit networks
|
https://scholar.google.com/scholar?cluster=16159327957430149358&hl=en&as_sdt=0,33
| 2
| 2,020
|
MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
| 747
|
cvpr
| 322
| 55
|
2023-06-03 02:43:56.878000
|
https://github.com/switchablenorms/CelebAMask-HQ
| 1,813
|
Maskgan: Towards diverse and interactive facial image manipulation
|
https://scholar.google.com/scholar?cluster=11254718545246006006&hl=en&as_sdt=0,47
| 46
| 2,020
|
Learning Memory-Guided Normality for Anomaly Detection
| 424
|
cvpr
| 74
| 34
|
2023-06-03 02:43:57.080000
|
https://github.com/cvlab-yonsei/MNAD
| 282
|
Learning memory-guided normality for anomaly detection
|
https://scholar.google.com/scholar?cluster=956898906864347055&hl=en&as_sdt=0,15
| 12
| 2,020
|
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