(CVPR'20 Oral) Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild

Point-NeRF: Point-based Neural Radiance Fields

A geometry-shader-based, global CUDA sorted high-performance 3D Gaussian Splatting rasterizer. Can achieve a 5-10x speedup in rendering compared to the vanialla diff-gaussian-rasterization.

pytorch memory track code

[ECCV2022] PETR: Position Embedding Transformation for Multi-View 3D Object Detection & [ICCV2023] PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

ICRA 2019 "FastDepth: Fast Monocular Depth Estimation on Embedded Systems"

Spherical CNNs

improves over nerf in 360 capture of unbounded scenes

Neural Surface reconstruction based on Instant-NGP. Efficient and customizable boilerplate for your research projects. Train NeuS in 10min!

[ECCV'20] Convolutional Occupancy Networks

CMake wrapper for conan C and C++ package manager

Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more.

SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation

SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation

MCAP is a modular, performant, and serialization-agnostic container file format, useful for pub/sub and robotics applications.

Code of single-view depth prediction algorithm on Internet Photos described in "MegaDepth: Learning Single-View Depth Prediction from Internet Photos, Z. Li and N. Snavely, CVPR 2018".

[CVPR'22 Oral] GMFlow: Learning Optical Flow via Global Matching

Code for GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose (CVPR 2018)

[ICCV 2023] StreamPETR: Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection

SOS IROS 2018 GOOGLE; StereoNet ECCV2018 GOOGLE; ActiveStereoNet ECCV2018 Oral GOOGLE; HITNET CVPR2021 GOOGLE；PLUME Uber ATG

Code for 'Stereo R-CNN based 3D Object Detection for Autonomous Driving' (CVPR 2019)

Code for "Neural 3D Reconstruction in the Wild", SIGGRAPH 2022 (Conference Proceedings)

【CVPR 2025 Highlight】MonSter: Marry Monodepth to Stereo Unleashes Power

The repository containing tools and information about the WoodScape dataset.

PyTorch Implementation of MVSNet