The code for the paper "Towards Compact 3D Representations via Point Feature Enhancement Masked Autoencoders" (AAAI'24).
☆38Dec 26, 2023Updated 2 years ago
Alternatives and similar repositories for AAAI24-PointFEMAE
Users that are interested in AAAI24-PointFEMAE are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- The code for the paper "Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models" (ICCV'23).☆111Dec 19, 2023Updated 2 years ago
- [NeurIPS 2024 Spotlight (Top 2.5%🏆)] PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders☆53Sep 1, 2025Updated 9 months ago
- The code for the paper "LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling" (NeurIPS'24).☆15Dec 25, 2024Updated last year
- [ICML 2023] Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining☆153Jul 21, 2024Updated last year
- ☆20Sep 27, 2024Updated last year
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- [ICCV-2025] Universal Adversarial Attack, Multimodal Adversarial Attacks, VLP models, Contrastive Learning, Cross-modal Perturbation Gene…☆36Jul 10, 2025Updated 11 months ago
- [ICLR 2023] Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?☆104Jul 1, 2024Updated last year
- [ECCV-2024] Transferable Targeted Adversarial Attack, CLIP models, Generative adversarial network, Multi-target attacks☆39Apr 23, 2025Updated last year
- A point cloud visualization repo☆97Oct 15, 2025Updated 8 months ago
- [ACM MM 2024] Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model☆161Sep 20, 2025Updated 8 months ago
- [ECCV-2024 oral] Source code for our paper "A Closer Look at GAN Priors: Exploiting Intermediate Features for Enhanced Model Inversion At…☆25Sep 22, 2024Updated last year
- [CVPR 2023] Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders☆230Aug 10, 2023Updated 2 years ago
- [ECCV2022] Masked Autoencoders for Point Cloud Self-supervised Learning☆630Mar 31, 2025Updated last year
- [ICCV 23] A Simple Vision Transformer for Weakly Semi-supervised 3D Object Detection☆13Apr 12, 2024Updated 2 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- [BMVC 2023] Backdoor Attack on Hash-based Image Retrieval via Clean-label Data Poisoning☆17Sep 1, 2023Updated 2 years ago
- (AAAI2024) Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models☆58May 19, 2024Updated 2 years ago
- [IEEE TPAMI] Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning☆390Apr 30, 2026Updated last month
- [ICCV 2023] Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models☆43Jul 30, 2024Updated last year
- [NeurIPS 2022] Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training☆226May 4, 2023Updated 3 years ago
- [CVPR2023] Official implementation of “PiMAE: Point cloud and Image Interactive Masked Autoencoders for 3D Object Detecion”☆139Dec 12, 2024Updated last year
- [NeurIPS 2023] PointGPT: Auto-regressively Generative Pre-training from Point Clouds☆245Jul 1, 2024Updated last year
- The code for the paper "Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning" (CVPR'25).☆15Sep 25, 2025Updated 8 months ago
- [NeurIPS 2024] PointMamba: A Simple State Space Model for Point Cloud Analysis☆543Mar 19, 2025Updated last year
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Self-Supervised Learning with Multi-View Rendering for 3D Point Cloud Analysis (ACCV 2022)☆11Jul 22, 2024Updated last year
- [NeurIPS2024] BoostAdapter: Improving Test-Time Adaptation via Regional Bootstrapping☆20Feb 28, 2026Updated 3 months ago
- Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding (ICLR 2023)☆22May 2, 2023Updated 3 years ago
- [WACV 2025] Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud☆46Mar 3, 2025Updated last year
- [NeurIPS 2023] VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation☆37Jun 27, 2024Updated last year
- [CVPR 2023] Backdoor Defense via Adaptively Splitting Poisoned Dataset☆50Apr 8, 2024Updated 2 years ago
- [GCPR 2023 | CVPR 2023 Workshop] Self-Supervised Representation Learning on Point Clouds☆101Jan 26, 2026Updated 4 months ago
- Implementation of the Apparent Ridges algorithm for 3D edge detection☆16Sep 28, 2020Updated 5 years ago
- ☆29Oct 4, 2024Updated last year
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- [NeurIPS 2024] Official implementation of the paper "Point-PRC: A Prompt Learning Based Regulation Framework for Generalizable Point Clou…☆17Mar 13, 2026Updated 3 months ago
- [CVPR 2025] MoST: Efficient Monarch Sparse Tuning for 3D Representation Learning☆21Sep 20, 2025Updated 8 months ago
- X-3D: Explicit 3D Structure Modeling for Point Cloud Recognition (CVPR2024)☆36Mar 26, 2024Updated 2 years ago
- The code for the paper "Efficient Self-Supervised Video Hashing with Selective State Spaces" (AAAI'25).☆23Aug 2, 2025Updated 10 months ago
- The code for the paper "Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval" (WWW'22, Oral).☆17Mar 8, 2022Updated 4 years ago
- [ECCV 2024] ShapeLLM: Universal 3D Object Understanding for Embodied Interaction☆237Oct 8, 2024Updated last year
- Code for "Language Models Can Learn from Verbal Feedback Without Scalar Rewards"☆65Jan 5, 2026Updated 5 months ago