arXiv Computer Vision
AdapToPASS: Ambiguity-aware Adaptive Spherical Transformer for Panoramic Semantic Segmentation
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arXiv Computer Vision
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TDFNet: Tri-projection Deformable Fusion Network for Panoramic Salient Object Detection
TDFNet introduces a Tri-projection Deformable Fusion Network that uses equirectangular, cube map, and tangent projections to mitigate geometric distortions in panoramic salient object detection. It incorporates a cross-projection deformable attention module for geometry-aware sampling and a latitude-guided fusion module that balances ERP and CMP features using spherical latitude priors. The network’s three-branch encoding preserves global continuity, local detail, and boundary precision, improving detection performance over existing projection-based methods.
arXiv Computer Vision
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Bridging Language and Spherical Space: Object-Centric Control for Text-to-Panorama Generation
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arXiv Computer Vision
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VCAR: Training-Free 3DGS Segmentation via View Completeness and Axis-Aware Boundary Refinement
arXiv:2608.30870v1 Announce Type: new Abstract: Semantic segmentation in 3D Gaussian Splatting (3DGS) is crucial for advancing 3D scene understanding. Existing methods predominantly rely on feature d...
arXiv AI
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OneCanvas: 3D Scene Understanding via Panoramic Reprojection
arXiv:2606. 19253v1 Announce Type: cross Abstract: Existing approaches to 3D scene understanding in Vision-Language Models (VLMs) either rely on complex, model-specific geometry encoders or large training budgets in pursuit of spatial reasoning.
arXiv Computer Vision
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PointGauss: Point Cloud-Guided Multi-Object Segmentation for Gaussian Splatting
arXiv:2508.00259v2 Announce Type: replace Abstract: While 3D Gaussian Splatting (3DGS) has established new standards for high-fidelity 3D scene modeling, interpreting massive, unstructured Gaussian p...
arXiv Computer Vision
1d ago
Geometric Distillation from Rectified Stereo: Leveraging Epipolar Cues for Monocular Depth
arXiv:2607.15600v2 Announce Type: replace Abstract: Monocular depth foundation models have demonstrated remarkable generalization capabilities across diverse environments. However, they continue to s...