OHTA

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)

[ICCV 2023] Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior

An Invitation to 3D Vision: A Tutorial for Everyone

Bundler Structure from Motion Toolkit

A simple baseline for 3d human pose estimation in tensorflow. Presented at ICCV 17.

?RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)

Get unified user avatar from social networks, including Instagram, SoundCloud, Telegram, Twitter, YouTube & more.

[NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

Cross-platform SDK for facial motion capture producing blendshapes and rigid head poses in 3D space in realtime from photos or videos.