FoundDP integrates DP-derived metric depth with ViT-based structural priors from monocular models, using feature alignment to mitigate defocus blur and improve depth in low-observability areas.
In: Proceedings of the Computer Vision and Pattern Recog- nition Conference
2 Pith papers cite this work. Polarity classification is still indexing.
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PAD synthesizes 3D geometry in observation space via depth unprojection as anchor to eliminate pose ambiguity in image-to-3D generation.
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FoundDP: Revisiting Weak Disparity Observability in Dual-Pixel Depth Estimation
FoundDP integrates DP-derived metric depth with ViT-based structural priors from monocular models, using feature alignment to mitigate defocus blur and improve depth in low-observability areas.
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Pose-Aware Diffusion for 3D Generation
PAD synthesizes 3D geometry in observation space via depth unprojection as anchor to eliminate pose ambiguity in image-to-3D generation.