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Matthew Tancik\ 1 , Ben Mildenhall\ 1 , Terrance Wang 1 , Divi Schmidt 1 , Pratul P. Srinivasan 2 , Jonathan T. Barron 2 , Ren Ng 1
The main features of tancik/learnit are: Generalization, Generalization Models.
Projects with overlapping indexed features include: zubair-irshad/neo-360 — Pytorch code for ICCV'23 paper. NEO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes. apchenstu/mvsnerf — [ICCV 2021] Our work presents a novel neural rendering approach that can efficiently reconstruct geometric and neural… autonomousvision/graf — Official code release for "GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis". alextrevithick/grf — 🔥 General Radiance Field (ICCV, 2021). haoyizhu/xnerf — [WACV 2023] XNeRF: Explicit Neural Radiance Field for Multi-Scene 360° Insufficient RGB-D Views. ruili3/know-your-neighbors — [CVPR 2024] 🏡Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning.
Official code release for "GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis"
ICCV 2021 Our work presents a novel neural rendering approach that can efficiently reconstruct geometric and neural radiance fields for view synthesis.
WACV 2023 XNeRF: Explicit Neural Radiance Field for Multi-Scene 360° Insufficient RGB-D Views
