GAPrompt++: Multi-Granular Geometry-Aware Point Cloud Prompt for 3D Vision Model
cs.CV
Submitted: 2026-09-17
Updated: 2026-09-17
Code: https://github.com/PKU-OV3-LAB/GAPromptPlus
Terminology
Sources
- The Power of Scale for Parameter-Efficient Prompt Tuning
- Prefix-Tuning: Optimizing Continuous Prompts for Generation
- Towards a Unified View of Parameter-Efficient Transfer Learning
- ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills
- Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
- ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
- DINOv3
- Harnessing Text-to-Image Diffusion Models for Point Cloud Self-Supervised Learning
- Exploring Visual Prompts for Adapting Large-Scale Models
- DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
- ShapeNet: An Information-Rich 3D Model Repository
- Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework
- BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models
- LoRA: Low-Rank Adaptation of Large Language Models
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