CATRF inserts standard codecs into the training loop of triplane radiance fields via straight-through estimation so the features adapt to codec distortions and achieve better rate-distortion performance for volumetric streaming.
Neural sparse voxel fields.Advances in Neural Information Processing Systems, 33:15651–15663,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
Long-LRM++ achieves real-time 14 FPS high-fidelity 360-degree scene reconstruction from 32-64 views by using semi-explicit Gaussians plus a light decoder, matching LaCT quality on DL3DV and improving depth prediction.
citing papers explorer
-
CATRF: Codec-Adaptive TriPlane Radiance Fields for Volumetric Content Delivery
CATRF inserts standard codecs into the training loop of triplane radiance fields via straight-through estimation so the features adapt to codec distortions and achieve better rate-distortion performance for volumetric streaming.
-
Long-LRM++: Preserving Fine Details in Feed-Forward Wide-Coverage Reconstruction
Long-LRM++ achieves real-time 14 FPS high-fidelity 360-degree scene reconstruction from 32-64 views by using semi-explicit Gaussians plus a light decoder, matching LaCT quality on DL3DV and improving depth prediction.