prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the Upernet-BiFormer-S (IN1k pretrain, Upernet 160k) model in the BiFormer: Vision Transformer with Bi-Level Routing Attention paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the UperNet Shuffle-B model in the Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ConvNeXt V1-L model in the ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DiNAT-Base (UperNet) model in the Dilated Neighborhood Attention Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ELSA-Swin-S model in the ELSA: Enhanced Local Self-Attention for Vision Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the SETR-MLA (160k, MS) model in the Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the VAN-Large (HamNet) model in the Visual Attention Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the HRViT-b3 (SegFormer, SS) model in the Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Twins-SVT-L (UperNet, ImageNet-1k pretrain) model in the Twins: Revisiting the Design of Spatial Attention in Vision Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the MogaNet-B (UperNet) model in the Efficient Multi-order Gated Aggregation Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Seg-B-Mask/16(MS, ViT-B) model in the Segmenter: Transformer for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the iBOT (ViT-B/16) model in the iBOT: Image BERT Pre-Training with Online Tokenizer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ConvNeXt-B model in the A ConvNet for the 2020s paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DiNAT-Small (UperNet) model in the Dilated Neighborhood Attention Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ConvNeXt V1-B model in the ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the NAT-Base model in the Neighborhood Attention Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Swin-B (UperNet, ImageNet-1k pretrain) model in the Swin Transformer: Hierarchical Vision Transformer using Shifted Windows paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Seg-B/8 (MS, ViT-B) model in the Segmenter: Transformer for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ConvNeXt-S model in the A ConvNet for the 2020s paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Light-Ham (VAN-Base) model in the Is Attention Better Than Matrix Decomposition? paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the NAT-Small model in the Neighborhood Attention Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DaViT-B model in the DaViT: Dual Attention Vision Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DAT-B (UperNet) model in the Vision Transformer with Deformable Attention paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the PatchConvNet-S60 (UperNet) model in the Augmenting Convolutional networks with attention-based aggregation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the MogaNet-S (UperNet) model in the Efficient Multi-order Gated Aggregation Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Shift-B (UperNet) model in the When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DPT-Hybrid model in the Vision Transformers for Dense Prediction paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the GC ViT-B model in the Global Context Vision Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the A2MIM (ViT-B) model in the Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the EfficientViT-B3 (r512) model in the EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DiNAT-Tiny (UperNet) model in the Dilated Neighborhood Attention Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the HRViT-b2 (SegFormer, SS) model in the Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the NAT-Tiny model in the Neighborhood Attention Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the XCiT-M24/8 (UperNet) model in the XCiT: Cross-Covariance Image Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ResNeSt-200 model in the ResNeSt: Split-Attention Networks paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DAT-S (UperNet) model in the Vision Transformer with Deformable Attention paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the GC ViT-S model in the Global Context Vision Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
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 ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the VAN-Large model in the Visual Attention Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the XCiT-S24/8 (UperNet) model in the XCiT: Cross-Covariance Image Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the MaskFormer(ResNet-101) model in the Per-Pixel Classification is Not All You Need for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the MAE (ViT-B, UperNet) model in the Masked Autoencoders Are Scalable Vision Learners paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the HRNetV2 + OCR + RMI (PaddleClas pretrained) model in the Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
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 ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Shift-S model in the When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the MogaNet-S (Semantic FPN) model in the Efficient Multi-order Gated Aggregation Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the SeMask (SeMask Swin-S FPN) model in the SeMask: Semantically Masked Transformers for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ResNeSt-269 model in the ResNeSt: Split-Attention Networks paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the UperNet Shuffle-T model in the Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the CondNet(ResNest-101) model in the CondNet: Conditional Classifier for Scene Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the tiny-MOAT-3 (IN-1K pretraining, single scale) model in the MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the CondNet(ResNet-101) model in the CondNet: Conditional Classifier for Scene Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DiNAT-Mini (UperNet) model in the Dilated Neighborhood Attention Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DCNAS model in the DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the XCiT-S24/8 (Semantic-FPN) model in the XCiT: Cross-Covariance Image Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ResNeSt-101 model in the ResNeSt: Split-Attention Networks paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the XCiT-M24/8 (Semantic-FPN) model in the XCiT: Cross-Covariance Image Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the HamNet (ResNet-101) model in the Is Attention Better Than Matrix Decomposition? paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Sequential Ensemble (DeepLabv3+) model in the Sequential Ensembling for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ConvNeXt-T model in the A ConvNet for the 2020s paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the VAN-Base (Semantic-FPN) model in the Visual Attention Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the XCiT-S12/8 (UperNet) model in the XCiT: Cross-Covariance Image Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the GC ViT-T model in the Global Context Vision Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the NAT-Mini model in the Neighborhood Attention Transformer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Shift-T model in the When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DaViT-T model in the DaViT: Dual Attention Vision Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the CPN(ResNet-101) model in the Context Prior for Scene Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the MultiMAE
(ViT-B) model in the MultiMAE: Multi-modal Multi-task Masked Autoencoders paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DRAN(ResNet-101) model in the Scene Segmentation with Dual Relation-aware Attention Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the PyConvSegNet-152 model in the Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DNL model in the Disentangled Non-Local Neural Networks paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ACNet (ResNet-101) model in the Adaptive Context Network for Scene Parsing paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ACNet
(ResNet-101) model in the Adaptive Context Network for Scene Parsing paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the HRViT-b1 (SegFormer, SS) model in the Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the OCR(HRNetV2-W48) model in the Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the SPNet (ResNet-101) model in the Strip Pooling: Rethinking Spatial Pooling for Scene Parsing paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Swin-T (UPerNet) MoBY model in the Self-Supervised Learning with Swin Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DAT-T (UperNet) model in the Vision Transformer with Deformable Attention paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the iBOT (ViT-S/16) model in the iBOT: Image BERT Pre-Training with Online Tokenizer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the EANet
(ResNet-101) model in the Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the OCR (ResNet-101) model in the Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Asymmetric ALNN model in the Asymmetric Non-local Neural Networks for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Light-Ham (VAN-Small, D=256) model in the Is Attention Better Than Matrix Decomposition? paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the LaU-regression-loss model in the Location-aware Upsampling for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the PSPNet model in the Pyramid Scene Parsing Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the tiny-MOAT-2 (IN-1K pretraining, single scale) model in the MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the CFNet(ResNet-101) model in the Co-Occurrent Features in Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the EncNet model in the Context Encoding for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the LaU-offset-loss model in the Location-aware Upsampling for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the EncNet + JPU model in the FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the SGR (ResNet-101) model in the Symbolic Graph Reasoning Meets Convolutions paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the XCiT-S12/8 (Semantic-FPN) model in the XCiT: Cross-Covariance Image Transformers paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Auto-DeepLab-L model in the Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the PSANet (ResNet-101) model in the PSANet: Point-wise Spatial Attention Network for Scene Parsing paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DSSPN (ResNet-101) model in the Dynamic-structured Semantic Propagation Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the PSPNet (ResNet-152) model in the Pyramid Scene Parsing Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the PSPNet
(ResNet-101) model in the Pyramid Scene Parsing Network paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the HRNetV2 model in the High-Resolution Representations for Labeling Pixels and Regions paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the SeMask (SeMask Swin-T FPN) model in the SeMask: Semantically Masked Transformers for Semantic Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the tiny-MOAT-1 (IN-1K pretraining, single scale) model in the MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
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