Multi-hypotheses Conditioned Point Cloud Diffusion for 3D Human Reconstruction from Occluded Image (NeurIPS 2024)

Point Transformers

[ECCV 2024] GenPose++: A generative category-level 6D object pose estimation and tracking approach proposed in Omni6DPose.

[ECCV 2024] Omni6DPose: A Benchmark and Model for Universal 6D Object Pose Estimation and Tracking

Conditional diffusion model to generate MNIST. Minimal script. Based on 'Classifier-Free Diffusion Guidance'.

A Tutorial for Diffusion Models

CVPR2024: Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose Estimation

code for the SE3 Transformers paper: https://arxiv.org/abs/2006.10503

Pytorch implementation of diffusion models on Lie Groups for 6D grasp pose generation https://sites.google.com/view/se3dif/home

SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose Estimation (Accepted by NeurIPS-2023)

Auto-encoding & Generating 3D Point-Clouds.

Self-Supervised Learning for Domain Adaptation on Point-Clouds

[ICCV '21] "Unsupervised Point Cloud Pre-training via Occlusion Completion"

(ICCV2023) IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformation

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

PyTorch implementation of Pointnet2/Pointnet++

Research report on 6D pose estimation

[CVPR 2024] Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)

A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion

(TPAMI 2023) Snowflake Point Deconvolution for Point Cloud Completion and Generation with Skip-Transformer

Papers and Datasets about Point Cloud.

Experiments on unsupervised point cloud reconstruction.

Geometric Latent Diffusion Models for 3D Molecule Generation