[CVPR 2024] Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
-
Updated
Jun 16, 2024 - Python
A point cloud is a set of data points in space. The points represent a 3D shape or object. Each point has its set of X, Y and Z coordinates.
[CVPR 2024] Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
This is the official code for the ESORICS 2024 paper "PointAPA: Towards Availability Poisoning Attacks in 3D Point Clouds".
PointMamba: A Simple State Space Model for Point Cloud Analysis
[ICLR 2024] AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation
Open3DIS: Open-vocabulary 3D Instance Segmentation with 2D Mask Guidance (CVPR 2024)
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
[ICML 2023] Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining
[ICLR 2023] Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
[IROS 2023] Open-Vocabulary Affordance Detection in 3d Point Clouds
PointCT: Point Central Transformer Network for Weakly-supervised Point Cloud Semantic Segmentation (WACV 2024)
pyntcloud is a Python library for working with 3D point clouds.
[ICCV 2023] Official implementation for "Label-Guided Knowledge Distillation for Continual Semantic Segmentation on 2D Images and 3D Point Clouds".
The official implementation of the "Hypernetwork approach to generating point clouds" paper
ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolution (CVPR 2023)
PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flows
GaPro: Box-Supervised 3D Point Cloud Instance Segmentation Using Gaussian Processes as Pseudo Labelers (ICCV 2023)
Create a 3D points cloud with Horn Schunck algorithm
Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)
New distributional and shape attacks on neural networks that process 3D point cloud data.
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org