cs.CV(2023-11-13)
📊 共 18 篇论文 | 🔗 7 篇有代码
🎯 兴趣领域导航
支柱九:具身大模型 (Embodied Foundation Models) (7 🔗3)
支柱三:空间感知与语义 (Perception & Semantics) (5 🔗2)
支柱二:RL算法与架构 (RL & Architecture) (3 🔗1)
支柱一:机器人控制 (Robot Control) (2)
支柱四:生成式动作 (Generative Motion) (1 🔗1)
🔬 支柱九:具身大模型 (Embodied Foundation Models) (7 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | What Large Language Models Bring to Text-rich VQA? | 提出基于大语言模型的文本丰富视觉问答解决方案 | large language model multimodal | ||
| 2 | Vision-Language Integration in Multimodal Video Transformers (Partially) Aligns with the Brain | 通过神经科学证据提升多模态视频变换器的语言-视觉整合能力 | multimodal | ||
| 3 | SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models | 提出SPHINX以解决多模态大语言模型的任务混合与视觉嵌入问题 | large language model | ✅ | |
| 4 | To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning | 提出LVIS-Instruct4V以解决视觉指令调优中的粗粒度问题 | large language model multimodal instruction following | ✅ | |
| 5 | GPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigation | 提出MM-Navigator以解决智能手机GUI导航问题 | multimodal | ✅ | |
| 6 | TTMFN: Two-stream Transformer-based Multimodal Fusion Network for Survival Prediction | 提出TTMFN以解决癌症生存预测中的多模态信息融合问题 | multimodal | ||
| 7 | Semantically Grounded QFormer for Efficient Vision Language Understanding | 提出高效的QFormer框架以优化视觉语言理解 | multimodal |
🔬 支柱三:空间感知与语义 (Perception & Semantics) (5 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 8 | Open-Vocabulary Video Anomaly Detection | 提出开放词汇视频异常检测以解决开放世界异常识别问题 | open-vocabulary open vocabulary large language model | ||
| 9 | DeepMetricEye: Metric Depth Estimation in Periocular VR Imagery | 提出DeepMetricEye以解决VR眼部深度估计问题 | depth estimation metric depth | ||
| 10 | NDDepth: Normal-Distance Assisted Monocular Depth Estimation and Completion | 提出NDDepth以解决单目深度估计与补全问题 | depth estimation monocular depth | ✅ | |
| 11 | $L_0$-Sampler: An $L_{0}$ Model Guided Volume Sampling for NeRF | 提出$L_0$-Sampler以优化NeRF的体积采样 | 3D reconstruction NeRF neural radiance field | ✅ | |
| 12 | Amodal Optical Flow | 提出Amodal Optical Flow以解决透明或遮挡物体的光流估计问题 | optical flow |
🔬 支柱二:RL算法与架构 (RL & Architecture) (3 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 13 | MonoDiffusion: Self-Supervised Monocular Depth Estimation Using Diffusion Model | 提出MonoDiffusion以解决自监督单目深度估计问题 | distillation depth estimation monocular depth | ✅ | |
| 14 | SpectralGPT: Spectral Remote Sensing Foundation Model | 提出SpectralGPT以解决光谱遥感数据处理不足的问题 | representation learning scene understanding foundation model | ||
| 15 | Regenerating Arbitrary Video Sequences with Distillation Path-Finding | 提出交互框架以生成任意视频序列,解决动画创作难题 | distillation |
🔬 支柱一:机器人控制 (Robot Control) (2 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 16 | Multi Sentence Description of Complex Manipulation Action Videos | 提出多句描述框架以解决复杂操作视频自动描述问题 | manipulation | ||
| 17 | Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud | 提出一种新方法以实现可变形物体的重建与分割 | manipulation |
🔬 支柱四:生成式动作 (Generative Motion) (1 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 18 | Story-to-Motion: Synthesizing Infinite and Controllable Character Animation from Long Text | 提出Story-to-Motion以解决长文本驱动的角色动画生成问题 | text-to-motion text-driven motion motion synthesis | ✅ |