Alternatives and similar repositories for RFNet

Users that are interested in RFNet are comparing it to the libraries listed below

• Tianxinhuang / PCDNet
  The codes for ECCV'22: Resolution-free Point Cloud Sampling Network with Data Distillation
  ☆18Updated 2 years ago
• Tianxinhuang / PCLossNet
  The codes for ECCV'22: Learning to Train a Point Cloud Reconstruction Network without Matching
  ☆10Updated 2 years ago
• guochengqian / Pix4Point
  Official implementation for [3DV 2024] `Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding`
  ☆47Updated 10 months ago
• A-suozhang / CodedVTR
  code of [CVPR22] CodedVTR: Codebook-based Sparse Voxel Transformer with Geometric Guidance
  ☆17Updated 2 years ago
• YBZh / MaskSurf
  Masked Surfel Prediction for Self-Supervised Point Cloud Learning
  ☆27Updated last year
• ocNflag / point2seq
  ☆67Updated 2 years ago
• leolyj / DsCML
  This is the code related to "Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Se…
  ☆49Updated 3 years ago
• WisconsinAIVision / MaskPoint
  [ECCV 2022] Masked Discrimination for Self-Supervised Learning on Point Clouds
  ☆94Updated 2 years ago
• zehuichen123 / NoiseDet
  [ICCV2023] NoiseDet: Learning from Noisy Data for Semi-Superivsed 3D Object Detection
  ☆21Updated 2 years ago
• XiaoshuiHuang / EPCL
  [AAAI 2024-Oral] EPCL: Frozen CLIP Transformer is An Efficient Point Cloud Encoder
  ☆31Updated last year
• Robertwyq / LSMOL
  [NeurIPS 2022] 4D Unsupervised Object Discovery
  ☆55Updated last year
• CVMI-Lab / SPS-Conv
  (NeurlPS 2022) Spatial Pruned Sparse Convolution for Efficient 3D Object Detection
  ☆63Updated 2 years ago
• hwcao17 / ASAP-Net
  Code for paper "ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation"
  ☆30Updated 4 years ago
• jiawei-ren / ModelNet-C
  [ICML 2022] Benchmarking and Analyzing Point Cloud Classification under Corruptions https://arxiv.org/abs/2202.03377
  ☆61Updated 11 months ago
• wangzy22 / SemAffiNet
  [CVPR 2022] SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation
  ☆45Updated 2 years ago
• XiwuChen / PRA-Net
  The source code of PRA-Net.
  ☆25Updated 3 years ago
• mako443 / Text2Pos-CVPR2022
  Code, dataset and models for our CVPR 2022 publication "Text2Pos"
  ☆45Updated 2 years ago
• wangzy22 / TAP
  [ICCV 2023] Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models
  ☆42Updated 9 months ago
• RunsenXu / MV-JAR
  [CVPR 2023] MV-JAR: Masked Voxel Jigsaw and Reconstruction for LiDAR-Based Self-Supervised Pre-Training
  ☆47Updated last year
• Divadi / DetMatch
  DetMatch: Two Teachers are Better Than One for Joint 2D and 3D Semi-Supervised Object Detection
  ☆36Updated last year
• CVMI-Lab / DODA
  (ECCV 2022) DODA: Data-oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation
  ☆49Updated 2 years ago
• Ivan-Tang-3D / Point-PEFT
  (AAAI2024) Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models
  ☆51Updated 11 months ago
• AlibabaResearch / rcp
  ☆25Updated 2 years ago
• runnanchen / Label-Free-Scene-Understanding
  ☆50Updated last year
• RunpeiDong / ACT
  [ICLR 2023] Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
  ☆101Updated 10 months ago
• VITA-Group / Simple3D-Former
  [Preprint 2022] “Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer?” by Yi Wang, Zhiwen Fan, Tianlong Chen, Hehe Fan, Zh…
  ☆61Updated 2 years ago
• LifeBeyondExpectations / ECCV22-PointMixer
  [ECCV 2022] Official pytorch implementation of the paper, "PointMixer: MLP-Mixer for Point Cloud Understanding"
  ☆106Updated last year
• hehefan / PSTNet2
  Implementation of the "Deep Hierarchical Representation of Point Cloud Videos via Spatio-Temporal Decomposition" paper.
  ☆17Updated 4 years ago
• Tsinghua-MARS-Lab / GeoMAE
  This is the official implementation of the paper - GeoMAE: Masked Geometric Target Prediction for Self-supervised Point Cloud Pre-Trainin…
  ☆69Updated last year
• wangzy22 / P2P
  [NeurIPS 2022 Spotlight] P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting
  ☆130Updated last year