Research map / 3D vision / 3D generation
Projecting Your View Attentively: Monocular Road Scene Layout Estimation via Cross-View Transformation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add MLP view projection to the vanilla encoder-decoder (ablation) | Proposed framework · KITTI 3D Object | mIOU (%): 22.31 -> 27.42 | Helped |
| Add cross-view correlation attention (ablation) | Proposed framework · KITTI 3D Object | mIOU (%): 27.42 -> 35.03 | Helped |
| Add cycle structure and cycle loss (ablation) | Proposed framework · KITTI 3D Object | mIOU (%): 35.03 -> 35.54 | Helped |
| Add feature selection to the cross-view transformer (ablation) | Proposed framework · KITTI 3D Object | mIOU (%): 35.54 -> 38.79 | Helped |
| Use original features X as key and cycled features X′′ as value in CVT (ablation) | Cross-view transformer · KITTI 3D Object | mIOU (%): 37.58 -> 38.79 | Helped |
| Use projected features X′ as both key and value instead of X and X′′ (ablation) | Cross-view transformer · KITTI 3D Object | mIOU (%): 38.79 -> 25.43 | Hurt |
| Use cycled features X′′ as both key and value instead of X and X′′ (ablation) | Cross-view transformer · KITTI 3D Object | mIOU (%): 38.79 -> 27.71 | Hurt |
| Use original features X as both key and value instead of X and X′′ (ablation) | Cross-view transformer · KITTI 3D Object | mIOU (%): 38.79 -> 35.13 | Hurt |
| Replace the context-aware discriminator with standard PatchGAN (ablation) | Proposed generator · Argoverse Vehicle | mIOU (%): 48.48 -> 47.07 | Hurt |
| Replace the context-aware discriminator with standard PatchGAN (ablation) | Proposed generator · Argoverse Vehicle | mAP (%): 64.04 -> 62.33 | Hurt |
| Add the context-aware discriminator instead of using no discriminator (ablation) | Proposed generator · Argoverse Vehicle | mIOU (%): 48.10 -> 48.48 | Helped |
| Add the context-aware discriminator instead of using no discriminator (ablation) | Proposed generator · Argoverse Vehicle | mAP (%): 61.94 -> 64.04 | Helped |
Closest papers by meaning
- Effective Multi-sensor Conditioning for Street-view Novel-view Synthesis (NeurIPS 2026 · similarity 0.87)
- SDGOCC: Semantic and Depth-Guided Bird's-Eye View Transformation for 3D Multimodal Occupancy Prediction (CVPR 2025 · similarity 0.87)
- StreetCrafter: Street View Synthesis with Controllable Video Diffusion Models (CVPR 2025 · similarity 0.86)
- LidaRF: Delving into Lidar for Neural Radiance Field on Street Scenes (CVPR 2024 · similarity 0.86)
- Unveiling the Hidden: Online Vectorized HD Map Construction with Clip-Level Token Interaction and Propagation (NeurIPS 2024 · similarity 0.85)
- MagicDrive: Street View Generation with Diverse 3D Geometry Control (ICLR 2024 · similarity 0.85)
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