arXiv Computer Vision
Cascaded Non-Line-of-Sight Imaging
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arXiv Computer Vision
Oct 19
Measurement-Adaptive Light-Cone Transform for Robust Non-Line-of-Sight Imaging
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arXiv Computer Vision
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Resolving Mixed Single-Photon LiDAR Returns for Foreground-View and Hidden Scene Reconstruction
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arXiv Computer Vision
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Memory-efficient GPU pipelines for real-time non-line-of-sight reconstruction
The paper presents memory‑efficient GPU pipelines that accelerate real‑time non‑line‑of‑sight (NLOS) reconstruction. By redesigning two wave‑based algorithms—f‑k migration and phasor‑fields—with fused kernels, warp‑level photon binning, batched transforms, CUDA graph replay, and selective FP16 storage, the authors achieve up to 42× speed‑ups over a reference streaming pipeline and 14× over the fastest published GPU baseline while reducing memory usage to as little as 2.5%. The work also includes an ablation study of implementation choices and introduces three denoising strategies that leverage the increased frame budget for future NLOS video processing.
Hugging Face Trending Papers
Jul 20
FF-ProCams: Feed-Forward Gaussian Splatting for Projector-Camera System
Projector-camera (ProCams) systems achieve active scene perception and controllable appearance manipulation via structured illumination, serving as a core infrastructure for spatial augmented reality, projection mapping, and surface reflectance acquisition. Existing inverse-rendering methods for ProCams deliver high-fidelity results but rely on time-consuming per-scene optimization, while mainstream feed-forward 3D reconstruction models produce baked appearance that cannot adapt to spatially varying projector illumination.
arXiv Computer Vision
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Sparse Light Field Sampling Improves Casual 3D and 4D Reconstruction
arXiv:2608.20602v1 Announce Type: cross Abstract: Many consumer smartphones, stereo cameras, and light field cameras record multiple synchronized viewpoints in a single exposure event. However, novel...
arXiv Computer Vision
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Spatiotemporal Flux Probing for Single-Photon Videography
arXiv:2609.22479v1 Announce Type: new Abstract: We address the problem of recovering high-speed videos from dynamic scenes under extreme photon sparsity. Existing methods rely on aggregating photon d...