LHDuan / ConDaFormerLinks
[NeurIPS'23] ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding
☆12Updated last year
Alternatives and similar repositories for ConDaFormer
Users that are interested in ConDaFormer are comparing it to the libraries listed below
Sorting:
- https://arxiv.org/abs/2104.02246 One Thing One Click (CVPR 2021) https://arxiv.org/abs/2303.14727 One Thing One Click++ (Arxiv)☆58Updated 2 years ago
- This is the code related to "Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation" (CVPR 2023)☆37Updated 2 years ago
- (ECCV 2022) DODA: Data-oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation☆49Updated 3 years ago
- [NeurIPS2022] Let Images Give You More: Point Cloud Cross-Modal Training for Shape Analysis☆73Updated 2 years ago
- This is a PyTorch implementation of PointMetaBase proposed by our paper "Meta Architecure for Point Cloud Analysis"☆105Updated 2 years ago
- This is the official repo for Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation (ICCV 23).☆50Updated last year
- ☆26Updated 3 years ago
- [NeurIPS 2022 Spotlight] P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting☆131Updated 2 years ago
- All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation (NeurIPS 2023)☆31Updated last year
- ☆41Updated 11 months ago
- ☆161Updated 2 years ago
- Geodesic-Former: a Geodesic-Guided Few-shot 3D Point Cloud Instance Segmenter (ECCV 2022)☆35Updated 11 months ago
- [ICCV 2023] Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models☆44Updated last year
- Official Implementation for "Mask-Attention-Free Transformer for 3D Instance Segmentation"☆72Updated 2 years ago
- 🍀 Official pytorch implementation of "ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation. Wu …☆45Updated last year
- The Experiment Code for Swin3D☆36Updated last year
- This is the official implementation of "Clustering based Point Cloud Representation Learning for 3D Analysis" (Accepted at ICCV 2023).☆44Updated last year
- The source code of PRA-Net.☆27Updated 4 years ago
- [CVPR 2024] This repo contains the code for our paper: Rethinking Few-shot 3D Point Cloud Semantic Segmentation☆110Updated 5 months ago
- PyTorch Implementation of "diffConv: Analyzing Irregular Point Clouds with an Irregular View" (ECCV'22)☆31Updated last year
- Learning Inter-Superpoint Affinity for Weakly Supervised 3D Instance Segmentation☆23Updated 2 years ago
- [ECCV 2022] Official pytorch implementation of the paper, "PointMixer: MLP-Mixer for Point Cloud Understanding"☆109Updated 2 years ago
- Official implementation for ECCV 2022 paper "3D Instances as 1D Kernels".☆56Updated 2 years ago
- Official implementation for [3DV 2024] `Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding`☆47Updated last year
- ☆16Updated last year
- [ICLR 2023] Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?☆102Updated last year
- [AAAI 2024-Oral] EPCL: Frozen CLIP Transformer is An Efficient Point Cloud Encoder☆33Updated last year
- Official PyTorch implementation of DeLA☆60Updated 2 months ago
- [CVPR 2022] SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation☆47Updated 3 years ago
- PDF: A Probability-Driven Framework for Open World 3D Point Cloud Semantic Segmentation [CVPR 2024]☆40Updated 2 months ago