cs.CV(2024-07-20)
📊 共 8 篇论文 | 🔗 2 篇有代码
🎯 兴趣领域导航
支柱九:具身大模型 (Embodied Foundation Models) (3 🔗1)
支柱一:机器人控制 (Robot Control) (2 🔗1)
支柱二:RL算法与架构 (RL & Architecture) (2)
支柱三:空间感知与语义 (Perception & Semantics) (1)
🔬 支柱九:具身大模型 (Embodied Foundation Models) (3 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | Automatic Generation of Fashion Images using Prompting in Generative Machine Learning Models | 提出基于提示工程的生成模型,用于自动生成时尚图像和描述。 | large language model chain-of-thought | ✅ | |
| 2 | Sim-CLIP: Unsupervised Siamese Adversarial Fine-Tuning for Robust and Semantically-Rich Vision-Language Models | Sim-CLIP:通过无监督对抗微调增强CLIP视觉编码器的鲁棒性和语义丰富性 | multimodal | ||
| 3 | Diffusion Models as Data Mining Tools | 利用扩散模型进行视觉数据挖掘,实现数据典型性分析与模式发现 | TAMP |
🔬 支柱一:机器人控制 (Robot Control) (2 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 4 | DISCO: Embodied Navigation and Interaction via Differentiable Scene Semantics and Dual-level Control | DISCO:提出基于可微场景语义和双层控制的具身导航与交互方法 | manipulation mobile manipulation affordance | ✅ | |
| 5 | FedPartWhole: Federated domain generalization via consistent part-whole hierarchies | FedPartWhole:通过一致的部分-整体层次结构实现联邦域泛化 | manipulation |
🔬 支柱二:RL算法与架构 (RL & Architecture) (2 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 6 | Adapt2Reward: Adapting Video-Language Models to Generalizable Robotic Rewards via Failure Prompts | Adapt2Reward:通过失败提示自适应视频-语言模型,实现通用机器人奖励函数 | reinforcement learning language conditioned | ||
| 7 | Scaling Up Single Image Dehazing Algorithm by Cross-Data Vision Alignment for Richer Representation Learning and Beyond | 提出基于跨数据视觉对齐的单图像去雾算法,提升表征学习能力 | representation learning |
🔬 支柱三:空间感知与语义 (Perception & Semantics) (1 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 8 | Realistic Surgical Image Dataset Generation Based On 3D Gaussian Splatting | 提出基于3D高斯溅射的真实感手术图像数据集生成方法,解决手术数据集匮乏问题。 | 3D gaussian splatting gaussian splatting splatting |