prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the PiT-B model in the Rethinking Spatial Dimensions of Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the DeepMAD-89M model in the DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Our SP-ViT-S model in the SP-ViT: Learning 2D Spatial Priors for Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Wave-ViT-S model in the Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the EfficientNetV2-S model in the EfficientNetV2: Smaller Models and Faster Training paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ASF-former-B model in the Adaptive Split-Fusion Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the DynamicViT-LV-M/0.8 model in the DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the TNT-B model in the Transformer in Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ResNeSt-200 model in the ResNeSt: Split-Attention Networks paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the AmoebaNet-A model in the Regularized Evolution for Image Classifier Architecture Search paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the CLCNet (S:B4+D:B7) model in the CLCNet: Rethinking of Ensemble Modeling with Classification Confidence Network paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ResNet-RS-270 (256 image res) model in the Revisiting ResNets: Improved Training and Scaling Strategies paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the SENet-350 model in the Bottleneck Transformers for Visual Recognition paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViT-B @224 (DeiT III) model in the DeiT III: Revenge of the ViT paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the SReT-S (384 res, ImageNet-1K only) model in the Sliced Recursive Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the DiNAT-Small model in the Dilated Neighborhood Attention Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Transformer local-attention (NesT-B) model in the Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the PVTv2-B4 model in the PVT v2: Improved Baselines with Pyramid Vision Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the CA-Swin-S (+MixPro) model in the MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ConvFormer-S18 (224 res, 21K) model in the MetaFormer Baselines for Vision paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the DAT-S model in the Vision Transformer with Deformable Attention paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the NAT-Small model in the Neighborhood Attention Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the QnA-ViT-Base model in the Learned Queries for Efficient Local Attention paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the RevBiFPN-S5 model in the RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Pyramid ViG-B model in the Vision GNN: An Image is Worth Graph of Nodes paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Twins-SVT-L model in the Twins: Revisiting the Design of Spatial Attention in Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the TransBoost-ViT-S model in the TransBoost: Improving the Best ImageNet Performance using Deep Transduction paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the XCiT-S model in the Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MaxViT-T (224res) model in the MaxViT: Multi-Axis Vision Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Wave-ViT-S model in the Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the LITv2-B model in the Fast Vision Transformers with HiLo Attention paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MultiGrain PNASNet (500px) model in the MultiGrain: a unified image embedding for classes and instances paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MAE (ViT-L) model in the Masked Autoencoders Are Scalable Vision Learners paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the PAT-B model in the Pattern Attention Transformer with Doughnut Kernel paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the FixEfficientNet-B2 model in the Fixing the train-test resolution discrepancy: FixEfficientNet paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the CAFormer-S18 (224 res) model in the MetaFormer Baselines for Vision paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the IPT-B model in the IncepFormer: Efficient Inception Transformer with Pyramid Pooling for Semantic Segmentation paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViTAE-B-Stage model in the ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ResT-Large model in the ResT: An Efficient Transformer for Visual Recognition paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the NFNet-F0 model in the High-Performance Large-Scale Image Recognition Without Normalization paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the SE-ResNeXt-101, 64x4d, S=2(320px) model in the Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ResMLP-B24/8 model in the ResMLP: Feedforward networks for image classification with data-efficient training paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the BoTNet T5 model in the Bottleneck Transformers for Visual Recognition paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the InternImage-T model in the InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the PatchConvNet-B60 model in the Augmenting Convolutional networks with attention-based aggregation paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViT-B (hMLP + BeiT) model in the Three things everyone should know about Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the UniFormer-S model in the UniFormer: Unifying Convolution and Self-attention for Visual Recognition paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViT-S @384 (DeiT III) model in the DeiT III: Revenge of the ViT paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MogaNet-S model in the Efficient Multi-order Gated Aggregation Network paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the GC ViT-T model in the Global Context Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ResNeXt-101 32x4d (semi-weakly sup.) model in the Billion-scale semi-supervised learning for image classification paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Sequencer2D-L model in the Sequencer: Deep LSTM for Image Classification paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the sMLPNet-B (ImageNet-1k) model in the Sparse MLP for Image Recognition: Is Self-Attention Really Necessary? paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the SE-ResNeXt-101, 64x4d, S=2(416px) model in the Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the CvT-21 (384 res) model in the CvT: Introducing Convolutions to Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the T2T-ViT-14|384 model in the Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the CeiT-S (384 finetune res) model in the Incorporating Convolution Designs into Visual Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the LV-ViT-S model in the All Tokens Matter: Token Labeling for Training Better Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MOAT-0 1K only model in the MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the EfficientNet-B5 model in the EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Transformer local-attention (NesT-S) model in the Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViL-Medium-D model in the Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the LITv2-M model in the Fast Vision Transformers with HiLo Attention paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Shift-B model in the When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Meta Pseudo Labels (ResNet-50) model in the Meta Pseudo Labels paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MultiGrain PNASNet (450px) model in the MultiGrain: a unified image embedding for classes and instances paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the TinyViT-11M-distill (21k) model in the TinyViT: Fast Pretraining Distillation for Small Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ReXNet-R_2.0 model in the Rethinking Channel Dimensions for Efficient Model Design paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the QnA-ViT-Small model in the Learned Queries for Efficient Local Attention paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the NAT-Tiny model in the Neighborhood Attention Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the SE-CoTNetD-101 model in the Contextual Transformer Networks for Visual Recognition paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Next-ViT-B model in the Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the PVTv2-B3 model in the PVT v2: Improved Baselines with Pyramid Vision Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the PatchConvNet-S120 model in the Augmenting Convolutional networks with attention-based aggregation paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViL-Base-D model in the Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the CycleMLP-B5 model in the CycleMLP: A MLP-like Architecture for Dense Prediction paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MultiGrain SENet154 (450px) model in the MultiGrain: a unified image embedding for classes and instances paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the DeepVit-L* (DeiT training recipe) model in the DeepViT: Towards Deeper Vision Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViT-S @224 (DeiT III, 21k) model in the DeiT III: Revenge of the ViT paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MKD ViT-S model in the Meta Knowledge Distillation paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViT-S@224 (cosub) model in the Co-training $2^L$ Submodels for Visual Recognition paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the PAT-S model in the Pattern Attention Transformer with Doughnut Kernel paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the TinyViT-21M model in the TinyViT: Fast Pretraining Distillation for Small Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the sMLPNet-S (ImageNet-1k) model in the Sparse MLP for Image Recognition: Is Self-Attention Really Necessary? paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the Pyramid ViG-M model in the Vision GNN: An Image is Worth Graph of Nodes paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the SwinV2-Ti model in the Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the gSwin-S model in the gSwin: Gated MLP Vision Model with Hierarchical Structure of Shifted Window paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MultiGrain SENet154 (400px) model in the MultiGrain: a unified image embedding for classes and instances paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the CvT-13 (384 res) model in the CvT: Introducing Convolutions to Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ResNet50_vd_ssld model in the Semi-Supervised Recognition under a Noisy and Fine-grained Dataset paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ConvFormer-S18 (224 res) model in the MetaFormer Baselines for Vision paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the MViT-B-16 model in the Multiscale Vision Transformers paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ResNeSt-101 model in the ResNeSt: Split-Attention Networks paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the RevBiFPN-S4 model in the RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ZenNAS (0.8ms) model in the Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the NASViT (supernet) model in the NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the DeiT-B (+MixPro) model in the MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the IPT-S model in the IncepFormer: Efficient Inception Transformer with Pyramid Pooling for Semantic Segmentation paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the ViL-Medium-W model in the Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
What metrics were used to measure the GFNet-H-B model in the Global Filter Networks for Image Classification paper on the ImageNet dataset? | Top 1 Accuracy, Number of params, GFLOPs, Top 5 Accuracy, Hardware Burden, Operations per network pass, Continual Weighted Accuracy |
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