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|---|---|---|---|---|---|---|---|---|---|---|---|
De-Rendering 3D Objects in the Wild
| 11
|
cvpr
| 9
| 3
|
2023-06-03 15:10:52.648000
|
https://github.com/brummi/derender3d
| 122
|
De-rendering 3D Objects in the Wild
|
https://scholar.google.com/scholar?cluster=1935620080686118847&hl=en&as_sdt=0,3
| 7
| 2,022
|
Global Sensing and Measurements Reuse for Image Compressed Sensing
| 3
|
cvpr
| 1
| 1
|
2023-06-03 15:10:52.841000
|
https://github.com/fze0012/mr-ccsnet
| 3
|
Global Sensing and Measurements Reuse for Image Compressed Sensing
|
https://scholar.google.com/scholar?cluster=6542901026232183837&hl=en&as_sdt=0,47
| 1
| 2,022
|
DETReg: Unsupervised Pretraining With Region Priors for Object Detection
| 50
|
cvpr
| 37
| 27
|
2023-06-03 15:10:53.036000
|
https://github.com/amirbar/detreg
| 309
|
Detreg: Unsupervised pretraining with region priors for object detection
|
https://scholar.google.com/scholar?cluster=10551610679278163665&hl=en&as_sdt=0,22
| 17
| 2,022
|
Learning ABCs: Approximate Bijective Correspondence for Isolating Factors of Variation With Weak Supervision
| 0
|
cvpr
| 7,286
| 1,013
|
2023-06-03 15:10:53.230000
|
https://github.com/google-research/google-research
| 29,545
|
Learning ABCs: Approximate Bijective Correspondence for isolating factors of variation with weak supervision
|
https://scholar.google.com/scholar?cluster=13054823983554523598&hl=en&as_sdt=0,47
| 726
| 2,022
|
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack
| 19
|
cvpr
| 2
| 0
|
2023-06-03 15:10:53.424000
|
https://github.com/liuye6666/adaptive_auto_attack
| 40
|
Practical evaluation of adversarial robustness via adaptive auto attack
|
https://scholar.google.com/scholar?cluster=11985714371020199162&hl=en&as_sdt=0,21
| 3
| 2,022
|
Online Continual Learning on a Contaminated Data Stream With Blurry Task Boundaries
| 19
|
cvpr
| 5
| 2
|
2023-06-03 15:10:53.618000
|
https://github.com/clovaai/puridiver
| 38
|
Online continual learning on a contaminated data stream with blurry task boundaries
|
https://scholar.google.com/scholar?cluster=4641150768738034616&hl=en&as_sdt=0,5
| 4
| 2,022
|
Learning To Imagine: Diversify Memory for Incremental Learning Using Unlabeled Data
| 8
|
cvpr
| 2
| 1
|
2023-06-03 15:10:53.812000
|
https://github.com/TOM-tym/Learn-to-Imagine
| 11
|
Learning to imagine: Diversify memory for incremental learning using unlabeled data
|
https://scholar.google.com/scholar?cluster=5026291664933280388&hl=en&as_sdt=0,33
| 1
| 2,022
|
Cross-View Transformers for Real-Time Map-View Semantic Segmentation
| 71
|
cvpr
| 58
| 32
|
2023-06-03 15:10:54.006000
|
https://github.com/bradyz/cross_view_transformers
| 424
|
Cross-view transformers for real-time map-view semantic segmentation
|
https://scholar.google.com/scholar?cluster=1491587142118840508&hl=en&as_sdt=0,3
| 15
| 2,022
|
Make It Move: Controllable Image-to-Video Generation With Text Descriptions
| 12
|
cvpr
| 7
| 2
|
2023-06-03 15:10:54.203000
|
https://github.com/youncy-hu/mage
| 28
|
Make it move: Controllable image-to-video generation with text descriptions
|
https://scholar.google.com/scholar?cluster=3516336906711406652&hl=en&as_sdt=0,1
| 1
| 2,022
|
VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks
| 81
|
cvpr
| 16
| 5
|
2023-06-03 15:10:54.405000
|
https://github.com/ylsung/vl_adapter
| 173
|
Vl-adapter: Parameter-efficient transfer learning for vision-and-language tasks
|
https://scholar.google.com/scholar?cluster=6414220699607528663&hl=en&as_sdt=0,5
| 7
| 2,022
|
Neural Points: Point Cloud Representation With Neural Fields for Arbitrary Upsampling
| 10
|
cvpr
| 33
| 13
|
2023-06-03 15:10:54.598000
|
https://github.com/wanquanf/neuralpoints
| 220
|
Neural points: point cloud representation with neural fields for arbitrary upsampling
|
https://scholar.google.com/scholar?cluster=7916530615220861431&hl=en&as_sdt=0,33
| 14
| 2,022
|
Fire Together Wire Together: A Dynamic Pruning Approach With Self-Supervised Mask Prediction
| 11
|
cvpr
| 2
| 2
|
2023-06-03 15:10:54.792000
|
https://github.com/selkerdawy/FTWT
| 6
|
Fire Together Wire Together: A Dynamic Pruning Approach with Self-Supervised Mask Prediction
|
https://scholar.google.com/scholar?cluster=916820794753097681&hl=en&as_sdt=0,43
| 1
| 2,022
|
FIFO: Learning Fog-Invariant Features for Foggy Scene Segmentation
| 11
|
cvpr
| 18
| 2
|
2023-06-03 15:10:54.986000
|
https://github.com/sohyun-l/fifo
| 77
|
Fifo: Learning fog-invariant features for foggy scene segmentation
|
https://scholar.google.com/scholar?cluster=10025377918833329993&hl=en&as_sdt=0,5
| 3
| 2,022
|
Accelerating Video Object Segmentation With Compressed Video
| 7
|
cvpr
| 4
| 2
|
2023-06-03 15:10:55.181000
|
https://github.com/kai422/covos
| 35
|
Accelerating video object segmentation with compressed video
|
https://scholar.google.com/scholar?cluster=6742993136450637773&hl=en&as_sdt=0,33
| 3
| 2,022
|
Bi-Directional Object-Context Prioritization Learning for Saliency Ranking
| 6
|
cvpr
| 0
| 2
|
2023-06-03 15:10:55.375000
|
https://github.com/grassbro/ocor
| 19
|
Bi-directional object-context prioritization learning for saliency ranking
|
https://scholar.google.com/scholar?cluster=3067181998464015249&hl=en&as_sdt=0,37
| 6
| 2,022
|
Unsupervised Visual Representation Learning by Online Constrained K-Means
| 9
|
cvpr
| 4
| 0
|
2023-06-03 15:10:55.570000
|
https://github.com/idstcv/coke
| 12
|
Unsupervised visual representation learning by online constrained k-means
|
https://scholar.google.com/scholar?cluster=5554234163511357212&hl=en&as_sdt=0,5
| 0
| 2,022
|
FastDOG: Fast Discrete Optimization on GPU
| 3
|
cvpr
| 5
| 0
|
2023-06-03 15:10:55.763000
|
https://github.com/lpmp/bdd
| 30
|
FastDOG: Fast discrete optimization on GPU
|
https://scholar.google.com/scholar?cluster=15262271901525322084&hl=en&as_sdt=0,5
| 2
| 2,022
|
What Do Navigation Agents Learn About Their Environment?
| 8
|
cvpr
| 3
| 0
|
2023-06-03 15:10:55.957000
|
https://github.com/allenai/isee
| 17
|
What do navigation agents learn about their environment?
|
https://scholar.google.com/scholar?cluster=5532012740599620331&hl=en&as_sdt=0,44
| 5
| 2,022
|
Self-Supervised Equivariant Learning for Oriented Keypoint Detection
| 6
|
cvpr
| 4
| 1
|
2023-06-03 15:10:56.151000
|
https://github.com/bluedream1121/REKD
| 49
|
Self-supervised equivariant learning for oriented keypoint detection
|
https://scholar.google.com/scholar?cluster=18376839789551926333&hl=en&as_sdt=0,5
| 2
| 2,022
|
Improving Adversarial Transferability via Neuron Attribution-Based Attacks
| 28
|
cvpr
| 2
| 0
|
2023-06-03 15:10:56.345000
|
https://github.com/jpzhang1810/naa
| 27
|
Improving adversarial transferability via neuron attribution-based attacks
|
https://scholar.google.com/scholar?cluster=3102917020132255936&hl=en&as_sdt=0,16
| 2
| 2,022
|
Focal and Global Knowledge Distillation for Detectors
| 74
|
cvpr
| 36
| 10
|
2023-06-03 15:10:56.539000
|
https://github.com/yzd-v/FGD
| 291
|
Focal and global knowledge distillation for detectors
|
https://scholar.google.com/scholar?cluster=14151291256828319904&hl=en&as_sdt=0,34
| 2
| 2,022
|
Instance-Wise Occlusion and Depth Orders in Natural Scenes
| 6
|
cvpr
| 1
| 1
|
2023-06-03 15:10:56.734000
|
https://github.com/POSTECH-CVLab/InstaOrder
| 26
|
Instance-wise occlusion and depth orders in natural scenes
|
https://scholar.google.com/scholar?cluster=17301949382953129928&hl=en&as_sdt=0,11
| 2
| 2,022
|
Learning To Prompt for Continual Learning
| 112
|
cvpr
| 33
| 4
|
2023-06-03 15:10:56.928000
|
https://github.com/google-research/l2p
| 278
|
Learning to prompt for continual learning
|
https://scholar.google.com/scholar?cluster=11127330701624169778&hl=en&as_sdt=0,22
| 7
| 2,022
|
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-Shot Learning
| 18
|
cvpr
| 7
| 6
|
2023-06-03 15:10:57.122000
|
https://github.com/stomachcold/hctransformers
| 42
|
Attribute surrogates learning and spectral tokens pooling in transformers for few-shot learning
|
https://scholar.google.com/scholar?cluster=17677971297733661657&hl=en&as_sdt=0,11
| 5
| 2,022
|
Contour-Hugging Heatmaps for Landmark Detection
| 3
|
cvpr
| 2
| 0
|
2023-06-03 15:10:57.316000
|
https://github.com/jfm15/contourhuggingheatmaps
| 7
|
Contour-Hugging Heatmaps for Landmark Detection
|
https://scholar.google.com/scholar?cluster=15311814784447519217&hl=en&as_sdt=0,10
| 1
| 2,022
|
Generalized Category Discovery
| 51
|
cvpr
| 13
| 8
|
2023-06-03 15:10:57.510000
|
https://github.com/sgvaze/generalized-category-discovery
| 138
|
Generalized category discovery
|
https://scholar.google.com/scholar?cluster=5154769386036347309&hl=en&as_sdt=0,33
| 14
| 2,022
|
FreeSOLO: Learning To Segment Objects Without Annotations
| 30
|
cvpr
| 31
| 11
|
2023-06-03 15:10:57.706000
|
https://github.com/nvlabs/freesolo
| 284
|
Freesolo: Learning to segment objects without annotations
|
https://scholar.google.com/scholar?cluster=3726545131723476858&hl=en&as_sdt=0,48
| 5
| 2,022
|
GANSeg: Learning To Segment by Unsupervised Hierarchical Image Generation
| 7
|
cvpr
| 1
| 1
|
2023-06-03 15:10:57.900000
|
https://github.com/xingzhehe/ganseg
| 14
|
Ganseg: Learning to segment by unsupervised hierarchical image generation
|
https://scholar.google.com/scholar?cluster=8381112320248526584&hl=en&as_sdt=0,44
| 1
| 2,022
|
Enhancing Adversarial Robustness for Deep Metric Learning
| 5
|
cvpr
| 1
| 0
|
2023-06-03 15:10:58.094000
|
https://github.com/cdluminate/robdml
| 18
|
Enhancing adversarial robustness for deep metric learning
|
https://scholar.google.com/scholar?cluster=6859977703388701066&hl=en&as_sdt=0,5
| 3
| 2,022
|
Dense Learning Based Semi-Supervised Object Detection
| 18
|
cvpr
| 8
| 12
|
2023-06-03 15:10:58.288000
|
https://github.com/chenbinghui1/dsl
| 83
|
Dense learning based semi-supervised object detection
|
https://scholar.google.com/scholar?cluster=3247052077202185212&hl=en&as_sdt=0,5
| 4
| 2,022
|
TransforMatcher: Match-to-Match Attention for Semantic Correspondence
| 9
|
cvpr
| 2
| 1
|
2023-06-03 15:10:58.483000
|
https://github.com/wookiekim/transformatcher
| 31
|
TransforMatcher: Match-to-Match Attention for Semantic Correspondence
|
https://scholar.google.com/scholar?cluster=15104802067612466032&hl=en&as_sdt=0,5
| 4
| 2,022
|
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation
| 52
|
cvpr
| 17
| 5
|
2023-06-03 15:10:58.677000
|
https://github.com/facebookresearch/HRViT
| 159
|
Multi-scale high-resolution vision transformer for semantic segmentation
|
https://scholar.google.com/scholar?cluster=7367405585260744735&hl=en&as_sdt=0,5
| 10
| 2,022
|
Optimal Correction Cost for Object Detection Evaluation
| 3
|
cvpr
| 0
| 1
|
2023-06-03 15:10:58.871000
|
https://github.com/mayu-ot/oc-cost
| 26
|
Optimal correction cost for object detection evaluation
|
https://scholar.google.com/scholar?cluster=2642922896219719634&hl=en&as_sdt=0,5
| 2
| 2,022
|
Robust Outlier Detection by De-Biasing VAE Likelihoods
| 4
|
cvpr
| 7,286
| 1,013
|
2023-06-03 15:10:59.065000
|
https://github.com/google-research/google-research
| 29,545
|
Robust outlier detection by de-biasing VAE likelihoods
|
https://scholar.google.com/scholar?cluster=11831436094055949436&hl=en&as_sdt=0,5
| 726
| 2,022
|
Artistic Style Discovery With Independent Components
| 3
|
cvpr
| 1
| 0
|
2023-06-03 15:10:59.259000
|
https://github.com/shelsin/artins
| 11
|
Artistic style discovery with independent components
|
https://scholar.google.com/scholar?cluster=11868555798863356936&hl=en&as_sdt=0,5
| 1
| 2,022
|
Convolution of Convolution: Let Kernels Spatially Collaborate
| 0
|
cvpr
| 2
| 0
|
2023-06-03 15:10:59.452000
|
https://github.com/genera1z/convolutionofconvolution
| 8
|
Convolution of Convolution: Let Kernels Spatially Collaborate
|
https://scholar.google.com/scholar?cluster=1747810192135914154&hl=en&as_sdt=0,5
| 1
| 2,022
|
Point2Seq: Detecting 3D Objects As Sequences
| 7
|
cvpr
| 5
| 1
|
2023-06-03 15:10:59.647000
|
https://github.com/ocnflag/point2seq
| 61
|
Point2seq: detecting 3D objects as sequences
|
https://scholar.google.com/scholar?cluster=6567908324401744618&hl=en&as_sdt=0,10
| 7
| 2,022
|
Look for the Change: Learning Object States and State-Modifying Actions From Untrimmed Web Videos
| 5
|
cvpr
| 4
| 0
|
2023-06-03 15:10:59.841000
|
https://github.com/soCzech/LookForTheChange
| 28
|
Look for the Change: Learning Object States and State-Modifying Actions from Untrimmed Web Videos
|
https://scholar.google.com/scholar?cluster=1537815863841327629&hl=en&as_sdt=0,5
| 4
| 2,022
|
HyperStyle: StyleGAN Inversion With HyperNetworks for Real Image Editing
| 96
|
cvpr
| 108
| 1
|
2023-06-03 15:11:00.036000
|
https://github.com/yuval-alaluf/hyperstyle
| 925
|
Hyperstyle: Stylegan inversion with hypernetworks for real image editing
|
https://scholar.google.com/scholar?cluster=13013295706162025578&hl=en&as_sdt=0,23
| 28
| 2,022
|
Video-Text Representation Learning via Differentiable Weak Temporal Alignment
| 3
|
cvpr
| 1
| 0
|
2023-06-03 15:11:00.231000
|
https://github.com/mlvlab/vt-twins
| 14
|
Video-text representation learning via differentiable weak temporal alignment
|
https://scholar.google.com/scholar?cluster=5591595499413413837&hl=en&as_sdt=0,5
| 0
| 2,022
|
Task-Adaptive Negative Envision for Few-Shot Open-Set Recognition
| 11
|
cvpr
| 4
| 3
|
2023-06-03 15:11:00.426000
|
https://github.com/shiyuanh/tane
| 15
|
Task-adaptive negative envision for few-shot open-set recognition
|
https://scholar.google.com/scholar?cluster=4099282274649852201&hl=en&as_sdt=0,5
| 6
| 2,022
|
Divide and Conquer: Compositional Experts for Generalized Novel Class Discovery
| 9
|
cvpr
| 1
| 0
|
2023-06-03 15:11:00.626000
|
https://github.com/muliyangm/comex
| 9
|
Divide and Conquer: Compositional Experts for Generalized Novel Class Discovery
|
https://scholar.google.com/scholar?cluster=17405901485879363588&hl=en&as_sdt=0,36
| 1
| 2,022
|
MixFormer: Mixing Features Across Windows and Dimensions
| 30
|
cvpr
| 1,087
| 190
|
2023-06-03 15:11:00.821000
|
https://github.com/PaddlePaddle/PaddleClas
| 4,860
|
Mixformer: Mixing features across windows and dimensions
|
https://scholar.google.com/scholar?cluster=16965662268880636582&hl=en&as_sdt=0,5
| 73
| 2,022
|
AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network
| 26
|
cvpr
| 10
| 1
|
2023-06-03 15:11:01.015000
|
https://github.com/wooseoklee4/ap-bsn
| 57
|
Ap-bsn: Self-supervised denoising for real-world images via asymmetric pd and blind-spot network
|
https://scholar.google.com/scholar?cluster=11985940273976088551&hl=en&as_sdt=0,5
| 2
| 2,022
|
Interpretable Part-Whole Hierarchies and Conceptual-Semantic Relationships in Neural Networks
| 6
|
cvpr
| 9
| 3
|
2023-06-03 15:11:01.229000
|
https://github.com/mmlab-cv/Agglomerator
| 24
|
Interpretable part-whole hierarchies and conceptual-semantic relationships in neural networks
|
https://scholar.google.com/scholar?cluster=17205796139419550527&hl=en&as_sdt=0,10
| 3
| 2,022
|
Not All Points Are Equal: Learning Highly Efficient Point-Based Detectors for 3D LiDAR Point Clouds
| 84
|
cvpr
| 50
| 18
|
2023-06-03 15:11:01.428000
|
https://github.com/yifanzhang713/ia-ssd
| 315
|
Not all points are equal: Learning highly efficient point-based detectors for 3d lidar point clouds
|
https://scholar.google.com/scholar?cluster=16655541821133235810&hl=en&as_sdt=0,5
| 4
| 2,022
|
DASO: Distribution-Aware Semantics-Oriented Pseudo-Label for Imbalanced Semi-Supervised Learning
| 17
|
cvpr
| 7
| 3
|
2023-06-03 15:11:01.622000
|
https://github.com/ytaek-oh/daso
| 55
|
DASO: Distribution-Aware Semantics-Oriented Pseudo-label for Imbalanced Semi-Supervised Learning
|
https://scholar.google.com/scholar?cluster=17144682580574038881&hl=en&as_sdt=0,5
| 2
| 2,022
|
MonoDTR: Monocular 3D Object Detection With Depth-Aware Transformer
| 42
|
cvpr
| 13
| 6
|
2023-06-03 15:11:01.816000
|
https://github.com/kuanchihhuang/monodtr
| 103
|
Monodtr: Monocular 3d object detection with depth-aware transformer
|
https://scholar.google.com/scholar?cluster=1805235227134475013&hl=en&as_sdt=0,33
| 8
| 2,022
|
CycleMix: A Holistic Strategy for Medical Image Segmentation From Scribble Supervision
| 12
|
cvpr
| 13
| 5
|
2023-06-03 15:11:02.010000
|
https://github.com/bwgzk/cyclemix
| 56
|
Cyclemix: A holistic strategy for medical image segmentation from scribble supervision
|
https://scholar.google.com/scholar?cluster=16924143345812990466&hl=en&as_sdt=0,5
| 3
| 2,022
|
CLIP-Forge: Towards Zero-Shot Text-To-Shape Generation
| 82
|
cvpr
| 31
| 7
|
2023-06-03 15:11:02.218000
|
https://github.com/autodeskailab/clip-forge
| 314
|
Clip-forge: Towards zero-shot text-to-shape generation
|
https://scholar.google.com/scholar?cluster=15450117600687919110&hl=en&as_sdt=0,5
| 17
| 2,022
|
Learning Graph Regularisation for Guided Super-Resolution
| 10
|
cvpr
| 7
| 0
|
2023-06-03 15:11:02.415000
|
https://github.com/prs-eth/graph-super-resolution
| 35
|
Learning graph regularisation for guided super-resolution
|
https://scholar.google.com/scholar?cluster=7635150475076541879&hl=en&as_sdt=0,15
| 2
| 2,022
|
Voxel Field Fusion for 3D Object Detection
| 22
|
cvpr
| 9
| 3
|
2023-06-03 15:11:02.609000
|
https://github.com/dvlab-research/vff
| 87
|
Voxel field fusion for 3d object detection
|
https://scholar.google.com/scholar?cluster=15196041616068317393&hl=en&as_sdt=0,33
| 3
| 2,022
|
IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo
| 28
|
cvpr
| 15
| 0
|
2023-06-03 15:11:02.805000
|
https://github.com/fangjinhuawang/itermvs
| 139
|
IterMVS: iterative probability estimation for efficient multi-view stereo
|
https://scholar.google.com/scholar?cluster=10217528380961894363&hl=en&as_sdt=0,47
| 9
| 2,022
|
Rethinking the Augmentation Module in Contrastive Learning: Learning Hierarchical Augmentation Invariance With Expanded Views
| 9
|
cvpr
| 0
| 0
|
2023-06-03 15:11:02.999000
|
https://github.com/zhangjb416/Hierarchical-Augmentation
| 7
|
Rethinking the augmentation module in contrastive learning: Learning hierarchical augmentation invariance with expanded views
|
https://scholar.google.com/scholar?cluster=4005108257678361504&hl=en&as_sdt=0,5
| 2
| 2,022
|
FedCorr: Multi-Stage Federated Learning for Label Noise Correction
| 15
|
cvpr
| 5
| 0
|
2023-06-03 15:11:03.194000
|
https://github.com/xu-jingyi/fedcorr
| 22
|
Fedcorr: Multi-stage federated learning for label noise correction
|
https://scholar.google.com/scholar?cluster=5669373680326837123&hl=en&as_sdt=0,33
| 1
| 2,022
|
Depth-Guided Sparse Structure-From-Motion for Movies and TV Shows
| 3
|
cvpr
| 5
| 0
|
2023-06-03 15:11:03.387000
|
https://github.com/amazon-research/small-baseline-camera-tracking
| 59
|
Depth-Guided Sparse Structure-from-Motion for Movies and TV Shows
|
https://scholar.google.com/scholar?cluster=1901915419593604514&hl=en&as_sdt=0,5
| 7
| 2,022
|
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing
| 10
|
cvpr
| 0
| 2
|
2023-06-03 15:11:03.581000
|
https://github.com/luost26/equivariant-orientedmp
| 22
|
Equivariant point cloud analysis via learning orientations for message passing
|
https://scholar.google.com/scholar?cluster=4920530705850028640&hl=en&as_sdt=0,5
| 6
| 2,022
|
Source-Free Object Detection by Learning To Overlook Domain Style
| 18
|
cvpr
| 4
| 6
|
2023-06-03 15:11:03.775000
|
https://github.com/Flashkong/Source-Free-Object-Detection-by-Learning-to-Overlook-Domain-Style
| 28
|
Source-free object detection by learning to overlook domain style
|
https://scholar.google.com/scholar?cluster=11890223003866230078&hl=en&as_sdt=0,20
| 2
| 2,022
|
Node Representation Learning in Graph via Node-to-Neighbourhood Mutual Information Maximization
| 9
|
cvpr
| 1
| 1
|
2023-06-03 15:11:03.969000
|
https://github.com/dongwei156/n2n
| 21
|
Node representation learning in graph via node-to-neighbourhood mutual information maximization
|
https://scholar.google.com/scholar?cluster=11746290513076855187&hl=en&as_sdt=0,5
| 2
| 2,022
|
One Step at a Time: Long-Horizon Vision-and-Language Navigation With Milestones
| 8
|
cvpr
| 1
| 1
|
2023-06-03 15:11:04.163000
|
https://github.com/chanhee-luke/m-track
| 8
|
One step at a time: Long-horizon vision-and-language navigation with milestones
|
https://scholar.google.com/scholar?cluster=17829230908017130659&hl=en&as_sdt=0,5
| 2
| 2,022
|
Point Cloud Pre-Training With Natural 3D Structures
| 9
|
cvpr
| 1
| 2
|
2023-06-03 15:11:04.357000
|
https://github.com/ryosuke-yamada/3dfractaldb
| 5
|
Point Cloud Pre-training with Natural 3D Structures
|
https://scholar.google.com/scholar?cluster=4232774493484775617&hl=en&as_sdt=0,5
| 3
| 2,022
|
SelfRecon: Self Reconstruction Your Digital Avatar From Monocular Video
| 49
|
cvpr
| 43
| 18
|
2023-06-03 15:11:04.551000
|
https://github.com/jby1993/selfreconcode
| 352
|
Selfrecon: Self reconstruction your digital avatar from monocular video
|
https://scholar.google.com/scholar?cluster=8410658971247413341&hl=en&as_sdt=0,5
| 22
| 2,022
|
Scene Consistency Representation Learning for Video Scene Segmentation
| 3
|
cvpr
| 9
| 2
|
2023-06-03 15:11:04.745000
|
https://github.com/TencentYoutuResearch/SceneSegmentation-SCRL
| 53
|
Scene Consistency Representation Learning for Video Scene Segmentation
|
https://scholar.google.com/scholar?cluster=2564075373785184208&hl=en&as_sdt=0,11
| 7
| 2,022
|
StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis
| 19
|
cvpr
| 3
| 0
|
2023-06-03 15:11:04.941000
|
https://github.com/zhihengli-UR/StyleT2I
| 34
|
Stylet2i: Toward compositional and high-fidelity text-to-image synthesis
|
https://scholar.google.com/scholar?cluster=6119835574966247948&hl=en&as_sdt=0,48
| 8
| 2,022
|
FineDiving: A Fine-Grained Dataset for Procedure-Aware Action Quality Assessment
| 14
|
cvpr
| 7
| 6
|
2023-06-03 15:11:05.135000
|
https://github.com/xujinglin/finediving
| 75
|
Finediving: A fine-grained dataset for procedure-aware action quality assessment
|
https://scholar.google.com/scholar?cluster=5125588138588766817&hl=en&as_sdt=0,5
| 3
| 2,022
|
Self-Supervised Models Are Continual Learners
| 45
|
cvpr
| 15
| 3
|
2023-06-03 15:11:05.329000
|
https://github.com/donkeyshot21/cassle
| 84
|
Self-supervised models are continual learners
|
https://scholar.google.com/scholar?cluster=8726502467009709179&hl=en&as_sdt=0,3
| 5
| 2,022
|
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart
| 9
|
cvpr
| 6
| 1
|
2023-06-03 15:11:05.523000
|
https://github.com/P2333/Rectified-Rejection
| 28
|
Two coupled rejection metrics can tell adversarial examples apart
|
https://scholar.google.com/scholar?cluster=9583967984455182755&hl=en&as_sdt=0,10
| 1
| 2,022
|
HEAT: Holistic Edge Attention Transformer for Structured Reconstruction
| 4
|
cvpr
| 10
| 4
|
2023-06-03 15:11:05.717000
|
https://github.com/woodfrog/heat
| 46
|
HEAT: Holistic Edge Attention Transformer for Structured Reconstruction
|
https://scholar.google.com/scholar?cluster=18409780889355359989&hl=en&as_sdt=0,14
| 7
| 2,022
|
Exploiting Explainable Metrics for Augmented SGD
| 2
|
cvpr
| 14
| 0
|
2023-06-03 15:11:05.911000
|
https://github.com/mahdihosseini/rmsgd
| 43
|
Exploiting Explainable Metrics for Augmented SGD
|
https://scholar.google.com/scholar?cluster=9604666184151717265&hl=en&as_sdt=0,47
| 4
| 2,022
|
REX: Reasoning-Aware and Grounded Explanation
| 6
|
cvpr
| 0
| 1
|
2023-06-03 15:11:06.105000
|
https://github.com/szzexpoi/rex
| 15
|
Rex: Reasoning-aware and grounded explanation
|
https://scholar.google.com/scholar?cluster=8689640944520847019&hl=en&as_sdt=0,5
| 1
| 2,022
|
VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolution
| 17
|
cvpr
| 18
| 4
|
2023-06-03 15:11:06.300000
|
https://github.com/picsart-ai-research/videoinr-continuous-space-time-super-resolution
| 215
|
Videoinr: Learning video implicit neural representation for continuous space-time super-resolution
|
https://scholar.google.com/scholar?cluster=3606765168614463405&hl=en&as_sdt=0,5
| 5
| 2,022
|
Improving Neural Implicit Surfaces Geometry With Patch Warping
| 41
|
cvpr
| 12
| 4
|
2023-06-03 15:11:06.494000
|
https://github.com/fdarmon/neuralwarp
| 188
|
Improving neural implicit surfaces geometry with patch warping
|
https://scholar.google.com/scholar?cluster=3623427518324463702&hl=en&as_sdt=0,32
| 8
| 2,022
|
EvUnroll: Neuromorphic Events Based Rolling Shutter Image Correction
| 7
|
cvpr
| 1
| 1
|
2023-06-03 15:11:06.689000
|
https://github.com/zxyemo/evunroll
| 24
|
EvUnroll: Neuromorphic events based rolling shutter image correction
|
https://scholar.google.com/scholar?cluster=4997635481202221489&hl=en&as_sdt=0,5
| 1
| 2,022
|
Gait Recognition in the Wild With Dense 3D Representations and a Benchmark
| 35
|
cvpr
| 12
| 2
|
2023-06-03 15:11:06.883000
|
https://github.com/Gait3D/Gait3D-Benchmark
| 93
|
Gait recognition in the wild with dense 3d representations and a benchmark
|
https://scholar.google.com/scholar?cluster=12338378403312062338&hl=en&as_sdt=0,5
| 5
| 2,022
|
AutoSDF: Shape Priors for 3D Completion, Reconstruction and Generation
| 50
|
cvpr
| 18
| 7
|
2023-06-03 15:11:07.078000
|
https://github.com/yccyenchicheng/AutoSDF
| 182
|
Autosdf: Shape priors for 3d completion, reconstruction and generation
|
https://scholar.google.com/scholar?cluster=11137881856007355965&hl=en&as_sdt=0,5
| 9
| 2,022
|
ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image Prior
| 3
|
cvpr
| 4
| 2
|
2023-06-03 15:11:07.272000
|
https://github.com/ozgurkara99/ISNAS-DIP
| 27
|
Isnas-dip: Image-specific neural architecture search for deep image prior
|
https://scholar.google.com/scholar?cluster=13979102315997014403&hl=en&as_sdt=0,5
| 3
| 2,022
|
A Unified Query-Based Paradigm for Point Cloud Understanding
| 11
|
cvpr
| 6
| 5
|
2023-06-03 15:11:07.467000
|
https://github.com/dvlab-research/deepvision3d
| 97
|
A unified query-based paradigm for point cloud understanding
|
https://scholar.google.com/scholar?cluster=15160520958505330608&hl=en&as_sdt=0,11
| 5
| 2,022
|
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values
| 9
|
cvpr
| 0
| 1
|
2023-06-03 15:11:07.661000
|
https://github.com/AhmedImtiazPrio/magnet-polarity
| 9
|
Polarity sampling: Quality and diversity control of pre-trained generative networks via singular values
|
https://scholar.google.com/scholar?cluster=13683632591453970770&hl=en&as_sdt=0,37
| 1
| 2,022
|
Learning From All Vehicles
| 37
|
cvpr
| 52
| 17
|
2023-06-03 15:11:07.854000
|
https://github.com/dotchen/LAV
| 336
|
Learning from all vehicles
|
https://scholar.google.com/scholar?cluster=16218506036464706349&hl=en&as_sdt=0,15
| 10
| 2,022
|
End-to-End Referring Video Object Segmentation With Multimodal Transformers
| 28
|
cvpr
| 67
| 15
|
2023-06-03 15:11:08.049000
|
https://github.com/mttr2021/MTTR
| 623
|
End-to-end referring video object segmentation with multimodal transformers
|
https://scholar.google.com/scholar?cluster=948851395326952237&hl=en&as_sdt=0,15
| 7
| 2,022
|
Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization
| 5
|
cvpr
| 1
| 0
|
2023-06-03 15:11:08.243000
|
https://github.com/djosix/IconFlow
| 18
|
Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization
|
https://scholar.google.com/scholar?cluster=1432476942087797797&hl=en&as_sdt=0,22
| 2
| 2,022
|
Towards Driving-Oriented Metric for Lane Detection Models
| 5
|
cvpr
| 3
| 1
|
2023-06-03 15:11:08.437000
|
https://github.com/asguard-uci/ld-metric
| 22
|
Towards driving-oriented metric for lane detection models
|
https://scholar.google.com/scholar?cluster=123008160880562675&hl=en&as_sdt=0,47
| 3
| 2,022
|
REGTR: End-to-End Point Cloud Correspondences With Transformers
| 44
|
cvpr
| 16
| 11
|
2023-06-03 15:11:08.631000
|
https://github.com/yewzijian/regtr
| 134
|
Regtr: End-to-end point cloud correspondences with transformers
|
https://scholar.google.com/scholar?cluster=1787546847961088663&hl=en&as_sdt=0,38
| 7
| 2,022
|
MAT: Mask-Aware Transformer for Large Hole Image Inpainting
| 61
|
cvpr
| 52
| 39
|
2023-06-03 15:11:08.825000
|
https://github.com/fenglinglwb/mat
| 427
|
Mat: Mask-aware transformer for large hole image inpainting
|
https://scholar.google.com/scholar?cluster=13226075639445229258&hl=en&as_sdt=0,16
| 7
| 2,022
|
XYDeblur: Divide and Conquer for Single Image Deblurring
| 6
|
cvpr
| 0
| 1
|
2023-06-03 15:11:09.019000
|
https://github.com/Seowon-Ji/XYDeblur
| 12
|
XYDeblur: divide and conquer for single image deblurring
|
https://scholar.google.com/scholar?cluster=1150348206342417431&hl=en&as_sdt=0,50
| 1
| 2,022
|
Neural 3D Scene Reconstruction With the Manhattan-World Assumption
| 39
|
cvpr
| 32
| 4
|
2023-06-03 15:11:09.213000
|
https://github.com/zju3dv/manhattan_sdf
| 413
|
Neural 3d scene reconstruction with the manhattan-world assumption
|
https://scholar.google.com/scholar?cluster=16772687487738165&hl=en&as_sdt=0,14
| 22
| 2,022
|
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
| 11
|
cvpr
| 1
| 5
|
2023-06-03 15:11:09.416000
|
https://github.com/4dvlab/stcrowd
| 39
|
Stcrowd: A multimodal dataset for pedestrian perception in crowded scenes
|
https://scholar.google.com/scholar?cluster=2069889439247779884&hl=en&as_sdt=0,5
| 3
| 2,022
|
Style-Based Global Appearance Flow for Virtual Try-On
| 16
|
cvpr
| 30
| 23
|
2023-06-03 15:11:09.610000
|
https://github.com/senhe/flow-style-vton
| 191
|
Style-based global appearance flow for virtual try-on
|
https://scholar.google.com/scholar?cluster=4991537933937419909&hl=en&as_sdt=0,33
| 7
| 2,022
|
IDEA-Net: Dynamic 3D Point Cloud Interpolation via Deep Embedding Alignment
| 4
|
cvpr
| 1
| 2
|
2023-06-03 15:11:09.804000
|
https://github.com/zengyiming-eamon/idea-net
| 15
|
Idea-net: Dynamic 3d point cloud interpolation via deep embedding alignment
|
https://scholar.google.com/scholar?cluster=9916120322274645032&hl=en&as_sdt=0,33
| 4
| 2,022
|
MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens
| 41
|
cvpr
| 7
| 3
|
2023-06-03 15:11:09.999000
|
https://github.com/hustvl/MSG-Transformer
| 73
|
Msg-transformer: Exchanging local spatial information by manipulating messenger tokens
|
https://scholar.google.com/scholar?cluster=12949437642882722873&hl=en&as_sdt=0,10
| 4
| 2,022
|
Semi-Supervised Video Semantic Segmentation With Inter-Frame Feature Reconstruction
| 2
|
cvpr
| 2
| 3
|
2023-06-03 15:11:10.193000
|
https://github.com/jfzhuang/ifr
| 24
|
Semi-supervised video semantic segmentation with inter-frame feature reconstruction
|
https://scholar.google.com/scholar?cluster=9308252690102339389&hl=en&as_sdt=0,33
| 2
| 2,022
|
UniCon: Combating Label Noise Through Uniform Selection and Contrastive Learning
| 23
|
cvpr
| 10
| 1
|
2023-06-03 15:11:10.388000
|
https://github.com/nazmul-karim170/unicon-noisy-label
| 42
|
Unicon: Combating label noise through uniform selection and contrastive learning
|
https://scholar.google.com/scholar?cluster=13840763414391094365&hl=en&as_sdt=0,11
| 2
| 2,022
|
Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection
| 11
|
cvpr
| 0
| 0
|
2023-06-03 15:11:10.582000
|
https://github.com/SDret/Pytorch-implementation-for-Rethinking-Reconstruction-Autoencoder-Based-Out-of-Distribution-Detection
| 4
|
Rethinking reconstruction autoencoder-based out-of-distribution detection
|
https://scholar.google.com/scholar?cluster=15354982576440685482&hl=en&as_sdt=0,21
| 1
| 2,022
|
Ray3D: Ray-Based 3D Human Pose Estimation for Monocular Absolute 3D Localization
| 17
|
cvpr
| 11
| 0
|
2023-06-03 15:11:10.776000
|
https://github.com/YxZhxn/Ray3D
| 95
|
Ray3D: ray-based 3D human pose estimation for monocular absolute 3D localization
|
https://scholar.google.com/scholar?cluster=10359759403461468779&hl=en&as_sdt=0,33
| 4
| 2,022
|
Amodal Segmentation Through Out-of-Task and Out-of-Distribution Generalization With a Bayesian Model
| 8
|
cvpr
| 5
| 1
|
2023-06-03 15:11:10.970000
|
https://github.com/yihongsun/bayesian-amodal
| 13
|
Amodal segmentation through out-of-task and out-of-distribution generalization with a bayesian model
|
https://scholar.google.com/scholar?cluster=12805769980060504688&hl=en&as_sdt=0,16
| 1
| 2,022
|
E-CIR: Event-Enhanced Continuous Intensity Recovery
| 8
|
cvpr
| 2
| 6
|
2023-06-03 15:11:11.165000
|
https://github.com/chensong1995/e-cir
| 37
|
E-cir: Event-enhanced continuous intensity recovery
|
https://scholar.google.com/scholar?cluster=8773035017781760200&hl=en&as_sdt=0,21
| 3
| 2,022
|
ASM-Loc: Action-Aware Segment Modeling for Weakly-Supervised Temporal Action Localization
| 29
|
cvpr
| 3
| 1
|
2023-06-03 15:11:11.359000
|
https://github.com/boheumd/asm-loc
| 29
|
ASM-Loc: action-aware segment modeling for weakly-supervised temporal action localization
|
https://scholar.google.com/scholar?cluster=16395330686982601785&hl=en&as_sdt=0,33
| 4
| 2,022
|
PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition
| 4
|
cvpr
| 4
| 3
|
2023-06-03 15:11:11.553000
|
https://github.com/Morpheus3000/PIE-Net
| 20
|
PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition
|
https://scholar.google.com/scholar?cluster=6666076693919758502&hl=en&as_sdt=0,33
| 2
| 2,022
|
Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes
| 7
|
cvpr
| 8
| 1
|
2023-06-03 15:11:11.747000
|
https://github.com/qq456cvb/CanonicalVoting
| 43
|
Canonical voting: Towards robust oriented bounding box detection in 3d scenes
|
https://scholar.google.com/scholar?cluster=6939279992146812577&hl=en&as_sdt=0,8
| 6
| 2,022
|
Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyond
| 16
|
cvpr
| 4
| 4
|
2023-06-03 15:11:11.942000
|
https://github.com/yuyi-sd/robust_rain_removal
| 27
|
Towards robust rain removal against adversarial attacks: A comprehensive benchmark analysis and beyond
|
https://scholar.google.com/scholar?cluster=18112822762459252278&hl=en&as_sdt=0,33
| 2
| 2,022
|
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