prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the ONE-PEACE model in the ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities 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 EVA model in the EVA: Exploring the Limits of Masked Visual Representation Learning at Scale 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 MAWS (ViT-2B) model in the The effectiveness of MAE pre-pretraining for billion-scale pretraining 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 M3I Pre-training (InternImage-H) model in the Towards All-in-one Pre-training via Maximizing Multi-modal Mutual Information 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-L/16 (384res, distilled from ViT-22B) model in the Scaling Vision Transformers to 22 Billion Parameters 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-H 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 MaxViT-XL (512res, JFT) 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 MaxViT-XL (384res, JFT) 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 MaxViT-L (512res, JFT) 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 NFNet-F4+ 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 MaxViT-L (384res, JFT) 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 MOAT-4 22K+1K 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 FD (CLIP ViT-L-336) model in the Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature 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 Last Layer Tuning with Newton Step (ViT-G/14)) model in the Differentially Private Image Classification from Features 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 TokenLearner L/8 (24+11) model in the TokenLearner: What Can 8 Learned Tokens Do for Images and Videos? 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-B (512res, JFT) 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 MViTv2-H (512 res, ImageNet-21k pretrain) model in the MViTv2: Improved Multiscale Vision Transformers for Classification and Detection 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-XL (512res, 21K) 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 MaxViT-B (384res, JFT) 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 ALIGN (EfficientNet-L2) model in the Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision 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-L2-475 (SAM) model in the Sharpness-Aware Minimization for Efficiently Improving Generalization 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/16 (384res, distilled from ViT-22B) model in the Scaling Vision Transformers to 22 Billion Parameters 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 BEiT-L (ViT; ImageNet-22K pretrain) model in the BEiT: BERT Pre-Training of Image 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 SWAG (ViT H/14) model in the Revisiting Weakly Supervised Pre-Training of Visual Perception 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 ViT-H/14 model in the An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale 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 CoAtNet-3 @384 model in the CoAtNet: Marrying Convolution and Attention for All Data Sizes 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-XL (384res, 21K) 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 mPLUG-2 model in the mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video 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 OpenCLIP ViT-H/14 model in the Reproducible scaling laws for contrastive language-image 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 FixEfficientNet-L2 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 ViTAE-H + MAE (448) model in the ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond 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-L (512res, 21K) 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 MViTv2-L (384 res, ImageNet-21k pretrain) model in the MViTv2: Improved Multiscale Vision Transformers for Classification and Detection 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 NoisyStudent (EfficientNet-L2) model in the Self-training with Noisy Student improves ImageNet 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 MaxViT-B (512res, 21K) 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 Top-k DiffSortNets (EfficientNet-L2) model in the Differentiable Top-k Classification 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 Adlik-ViT-SG+Swin_large+Convnext_xlarge(384) model in the A ConvNet for the 2020s 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 V-MoE-H/14 (Every-2) model in the Scaling Vision with Sparse Mixture of Experts 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-L (384res, 21K) 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 Unicom (ViT-L/14@336px) (Finetuned) model in the Unicom: Universal and Compact Representation Learning for Image Retrieval 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 PeCo (ViT-H, 448) model in the PeCo: Perceptual Codebook for BERT Pre-training 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 MaxViT-B (384res, 21K) 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 V-MoE-H/14 (Last-5) model in the Scaling Vision with Sparse Mixture of Experts 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 dBOT ViT-H (CLIP as Teacher) model in the Exploring Target Representations for Masked Autoencoders 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-B36 (384 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 VIT-H/14 model in the Scaling Vision with Sparse Mixture of Experts 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-H@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 InternImage-XL 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 MViTv2-H (mageNet-21k pretrain) model in the MViTv2: Improved Multiscale Vision Transformers for Classification and Detection 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 Mixer-H/14 (JFT-300M pre-train) model in the MLP-Mixer: An all-MLP Architecture 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 dBOT ViT-L (CLIP as Teacher) model in the Exploring Target Representations for Masked Autoencoders 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-XL (384res) 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 VAN-B6 (22K, 384res) model in the Visual Attention 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 RepLKNet-XL model in the Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs 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 ConvNeXt-XL (ImageNet-22k) model in the A ConvNet for the 2020s 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-H, 448) 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 ViT-L/16 model in the An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale 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 HorNet-L (GF) model in the HorNet: Efficient High-Order Spatial Interactions with Recursive Gated 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 InternImage-L 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 ConvFormer-B36 (384 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 BiT-L (ResNet) model in the Big Transfer (BiT): General 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 PeCo (ViT-H, 224) model in the PeCo: Perceptual Codebook for BERT Pre-training 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 ViT-L@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 CAFormer-M36 (384 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 CSWin-L (384 res,ImageNet-22k pretrain) model in the CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows 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 DaViT-L (ImageNet-22k) model in the DaViT: Dual Attention 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 DiNAT-Large (11x11ks; 384res; Pretrained on IN22K@224) 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 V-MoE-L/16 (Every-2) model in the Scaling Vision with Sparse Mixture of Experts 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-Large (384x384; Pretrained on ImageNet-22K @ 224x224) 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 data2vec 2.0 model in the Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language 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-B36 (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 UniNet-B6 model in the UniNet: Unified Architecture Search with Convolution, Transformer, and MLP 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_s-Large (384res; Pretrained on IN22K@224) 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 Swin-L (384 res, ImageNet-22k pretrain) model in the Swin Transformer: Hierarchical Vision Transformer using Shifted Windows 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 VOLO-D5+HAT model in the Improving Vision Transformers by Revisiting High-frequency Components 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 (PolyLoss) model in the PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions 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 ELSA-VOLO-D5 (512*512) model in the ELSA: Enhanced Local Self-Attention 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 Bamboo (Bamboo-H) model in the A Study on Transformer Configuration and Training Objective 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 Swin-L@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 FixEfficientNet-B7 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 FAN-L-Hybrid++ model in the Understanding The Robustness 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 SwinV2-B model in the Swin Transformer V2: Scaling Up Capacity and Resolution 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 VOLO-D5 model in the VOLO: Vision Outlooker 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 PatchConvNet-L120-21k-384 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 16-TokenLearner B/16 (21) model in the TokenLearner: What Can 8 Learned Tokens Do for Images and Videos? 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+DAT (ViT-H) model in the Enhance the Visual Representation via Discrete Adversarial 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 UniNet-B5 model in the UniNet: Unified Architecture Search with Convolution, Transformer, and MLP 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 VAN-B5 (22K, 384res) model in the Visual Attention 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 ConvFormer-B36 (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 MAE (ViT-H) 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 Hiera-H model in the Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles 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-S36 (384 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 ConvFormer-M36 (384 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 NoisyStudent (EfficientNet-B7) model in the Self-training with Noisy Student improves ImageNet 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 DaViT-B (ImageNet-22k) model in the DaViT: Dual Attention 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 EfficientNetV2-L (21k) 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 VOLO-D4 model in the VOLO: Vision Outlooker 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-F5 w/ SAM w/ augmult=16 model in the Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error 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 µ2Net (ViT-L/16) model in the An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems 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 @384 (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 |
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