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GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add GP Block in place of window attention (ablation) | window-attention GPViT (L1) · ImageNet-1K | Top-1 Acc: 78.1 -> 79.8 | Helped |
| add GP Block on top of LePE attention (ablation) | LePE-attention GPViT (L1) · ImageNet-1K | Top-1 Acc: 79.5 -> 80.5 | Helped |
| add GP Block on top of window attention (ablation) | window-attention GPViT (L1) · ADE20K SegFormer | mIoU: 41.7 -> 45.5 | Helped |
| add GP Block on top of LePE attention (ablation) | LePE-attention GPViT (L1) · ADE20K SegFormer | mIoU: 46.2 -> 46.9 | Helped |
| replace local attention with convolution propagation blocks (ablation) | GPViT (window and LePE attention) · ImageNet-1K | Top-1 Acc: 78.2 -> 75.8 (window); 79.5 -> 77.7 (LePE) | Hurt |
| replace GP Block with global attention (ablation) | GPViT (LePE attention) · ImageNet-1K | Top-1 Acc: 80.4 vs 80.5 for GP Block at ~10x FLOPs (62G vs 34G ADE20K) | Mixed |
| use shifted window attention instead of GP Block (ablation) | window-attention GPViT · ADE20K SegFormer | mIoU: 41.7 -> 40.7 | Hurt |
| remove group propagation (grouping and ungrouping only) (ablation) | GP Block · ImageNet-1K | Top-1 Acc: 80.5 -> 79.8 | Hurt |
| use self-attention instead of MLPMixer for group propagation (ablation) | GP Block · ImageNet-1K | Top-1 Acc: 80.5 -> 80.7 at higher FLOPs (6.2G vs 5.8G) | Helped |
| increase patch resolution (patch 16 to 8) with global self-attention (ablation) | ViT-D216 · ImageNet-1K | Top-1 Acc: 77.4 -> 79.2 | Helped |
| GPViT-L1 vs Swin-B backbone in Mask R-CNN 1x | GPViT-L1 · COCO Mask R-CNN 1x | AP^bb: 45.5 -> 48.1 | Helped |
| GPViT-L3 vs Swin-B on ADE20K UperNet | GPViT-L3 · ADE20K UperNet | mIoU: 49.7 -> 51.7 | Helped |
Closest papers by meaning
- GroupViT: Semantic Segmentation Emerges From Text Supervision (CVPR 2022 · similarity 0.91)
- Green Hierarchical Vision Transformer for Masked Image Modeling (NeurIPS 2022 · similarity 0.88)
- AdaViT: Adaptive Vision Transformers for Efficient Image Recognition (CVPR 2022 · similarity 0.87)
- Instance-Aware Group Quantization for Vision Transformers (CVPR 2024 · similarity 0.87)
- Perceptual Group Tokenizer: Building Perception with Iterative Grouping (ICLR 2024 · similarity 0.86)
- TGBFormer: Transformer-GraphFormer Blender Network for Video Object Detection (AAAI 2025 · similarity 0.86)
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