prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the PointCNN model in the Point Transformer paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
What metrics were used to measure the DeepGCN model in the DeepGCNs: Making GCNs Go as Deep as CNNs paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
What metrics were used to measure the SegCloud model in the SEGCloud: Semantic Segmentation of 3D Point Clouds paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
What metrics were used to measure the PointNet model in the Point Transformer paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
What metrics were used to measure the PCCN model in the Deep Parametric Continuous Convolutional Neural Networks paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
What metrics were used to measure the TangentConv model in the Tangent Convolutions for Dense Prediction in 3D paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
What metrics were used to measure the PointNet model in the PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
What metrics were used to measure the PointWeb model in the PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
What metrics were used to measure the PointCNN model in the PointCNN: Convolution On X-Transformed Points paper on the S3DIS Area5 dataset? | mIoU, mAcc, oAcc, FLOPs, Number of params |
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 ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
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 ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
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 ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the BEiT-3 model in the Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
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 ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ViT-Adapter-L (Mask2Former, BEiTv2 pretrain) model in the Vision Transformer Adapter for Dense Predictions paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the FD-SwinV2-G model in the Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the RevCol-H (Mask2Former) model in the Reversible Column Networks paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the MasK DINO (SwinL, multi-scale) model in the Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ViT-Adapter-L (Mask2Former, BEiT pretrain) model in the Vision Transformer Adapter for Dense Predictions paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the DINOv2 (ViT-g/14 frozen model, w/ ViT-Adapter + Mask2former) model in the DINOv2: Learning Robust Visual Features without Supervision paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the SwinV2-G(UperNet) model in the Swin Transformer V2: Scaling Up Capacity and Resolution paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the FocalNet-L (Mask2Former) model in the Focal Modulation Networks paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ViT-Adapter-L (UperNet, BEiT pretrain) model in the Vision Transformer Adapter for Dense Predictions paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the RSSeg-ViT-L (BEiT pretrain) model in the Representation Separation for Semantic Segmentation with 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 SegViT-v2 (BEiT-v2-Large) model in the SegViTv2: Exploring Efficient and Continual Semantic Segmentation with Plain 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 SeMask (SeMask Swin-L FaPN-Mask2Former) 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 SeMask (SeMask Swin-L MSFaPN-Mask2Former) 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 DiNAT-L (Mask2Former) 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 HorNet-L (Mask2Former) model in the HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Mask2Former (SwinL-FaPN) model in the Masked-attention Mask Transformer for Universal 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 FASeg (SwinL) model in the Dynamic Focus-aware Positional Queries 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 RR (BEiT-L) model in the Region Rebalance for Long-Tailed 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 MOAT-4 (IN-22K 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 Frozen Backbone, SwinV2-G-ext22K (Mask2Former) model in the Could Giant Pretrained Image Models Extract Universal Representations? 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-L Mask2Former) 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 Mask2Former (SwinL) model in the Masked-attention Mask Transformer for Universal 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 SenFormer (BEiT-L) model in the Efficient Self-Ensemble 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 BEiT-L (ViT+UperNet) model in the BEiT: BERT Pre-Training of 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 SeMask(SeMask Swin-L MSFaPN-Mask2Former, single-scale) 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 FaPN (MaskFormer, Swin-L, ImageNet-22k pretrain) model in the FaPN: Feature-aligned Pyramid Network for Dense Image Prediction paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the MOAT-3 (IN-22K 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 Mask2Former (Swin-L-FaPN) model in the Masked-attention Mask Transformer for Universal 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 SeMask (SeMask Swin-L MaskFormer) 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 dBOT ViT-L (CLIP) model in the Exploring Target Representations for 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 Mask2Former+CBL(Swin-B) model in the Conditional Boundary Loss 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 TADP model in the Text-image Alignment for Diffusion-based Perception paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the CSWin-L (UperNet, ImageNet-22k pretrain) model in the CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the Focal-L (UperNet, ImageNet-22k pretrain) model in the Focal Self-attention for Local-Global Interactions 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 InternImage-XL 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 dBOT ViT-L model in the Exploring Target Representations for 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 Mask2Former(Swin-B) model in the Masked-attention Mask Transformer for Universal 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 ConvNeXt V2-H (FCMAE) 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-Large (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 MaskFormer+CBL(Swin-B) model in the Conditional Boundary Loss 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 MOAT-2 (IN-22K 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 CAE (ViT-L, UperNet) model in the Context Autoencoder for Self-Supervised Representation Learning paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the VAN-B6 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 DiNAT_s-Large (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 DDP (Swin-L, step-3) model in the DDP: Diffusion Model for Dense Visual Prediction paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the PatchDiverse + Swin-L (multi-scale test, upernet, ImageNet22k pretrain) model in the Vision Transformers with Patch Diversification paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the VOLO-D5 model in the VOLO: Vision Outlooker 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 K-Net model in the K-Net: Towards Unified 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 GPaCo (Swin-L) model in the Generalized Parametric Contrastive Learning paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the SenFormer (Swin-L) model in the Efficient Self-Ensemble 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 Swin V2-H 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 InternImage-L 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 ConvNeXt-XL++ 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 Sequential Ensemble (SegFormer) 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 MogaNet-XL (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 MaskFormer(Swin-B) 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 ConvNeXt-L++ 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 SwinV2-G-HTC++ Liu et al. ([2021a]) model in the Swin Transformer V2: Scaling Up Capacity and Resolution paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the ConvNeXt V2-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 Seg-L-Mask/16 (MS) 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 MAE (ViT-L, 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 SeMask (SeMask Swin-L 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 Swin-L (UperNet, ImageNet-22k 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 Swin-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 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 PatchConvNet-L120 (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 dBOT ViT-B (CLIP) model in the Exploring Target Representations for 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 PatchConvNet-B120
(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 Swin-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 ConvNeXt V2-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 LV-ViT-L (UperNet, MS) model in the All Tokens Matter: Token Labeling for Training Better 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 SegFormer-B5 model in the SegFormer: Simple and Efficient Design for Semantic Segmentation 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 BiFormer-B (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 ConvNeXt V2-L (Supervised) 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 Light-Ham (VAN-Huge) 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 CrossFormer (ImageNet1k-pretrain, UPerNet, multi-scale test) model in the CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the InternImage-B 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 ActiveMLP-L(UperNet) model in the Active Token Mixer paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
What metrics were used to measure the SegFormer-B4 model in the SegFormer: Simple and Efficient Design for Semantic Segmentation 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 PatchConvNet-B60 (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 Light-Ham (VAN-Large) 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 TEC (Vit-B, Upernet) model in the Towards Sustainable Self-supervised Learning 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-B 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 InternImage-S 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 MogaNet-L (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 dBOT ViT-B model in the Exploring Target Representations for Masked Autoencoders paper on the ADE20K dataset? | Validation mIoU, Test Score, Params (M), GFLOPs (512 x 512), GFLOPs |
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