| 1 |
From Seeing to Experiencing: Scaling Navigation Foundation Models with Reinforcement Learning |
提出S2E框架以提升导航基础模型的交互能力 |
reinforcement learning 3D gaussian splatting gaussian splatting |
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| 2 |
Masked and Predictive Self-Supervised Foundation Models for 3D Brain MRI |
提出自监督基础模型以提升3D脑MRI疾病检测效果 |
JEPA Joint-Embedding Predictive Architecture joint-embedding predictive architecture |
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| 3 |
Radar-Guided Polynomial Fitting for Metric Depth Estimation |
提出POLAR以解决单目深度估计的度量深度转换问题 |
MAE depth estimation monocular depth |
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| 4 |
PaLMR: Towards Faithful Visual Reasoning via Multimodal Process Alignment |
提出PaLMR以解决多模态推理过程不一致问题 |
reinforcement learning reward design large language model |
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| 5 |
GeoWorld-VLM: Geometry from World Models for Vision-Language Models |
提出GeoWorld-VLM以解决视觉语言模型的空间关系识别问题 |
world model world models teacher-student |
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| 6 |
V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning |
提出V-JEPA 2.1以解决视频自监督学习中的密集特征学习问题 |
world model world models JEPA |
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| 7 |
Periodic-MAE: Periodic Video Masked Autoencoder for rPPG Estimation |
提出Periodic-MAE以解决rPPG估计中的视频信号表示问题 |
representation learning masked autoencoder MAE |
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| 8 |
AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation |
提出AudioX-Turbo以解决多模态音频生成效率问题 |
flow matching teacher-student distillation |
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| 9 |
Iterative Tool Usage Exploration for Multimodal Agents via Step-wise Preference Tuning |
提出SPORT方法以解决多模态智能体工具使用探索问题 |
reinforcement learning multimodal |
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| 10 |
MoVerse: Real-Time Video World Modeling with Panoramic Gaussian Scaffold |
提出MoVerse以解决实时视频世界建模问题 |
world model world models |
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| 11 |
VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models |
提出VISA以解决3D占用世界模型中的语义审计问题 |
world model world models |
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| 12 |
Analyzing and Improving Fine-grained Preference Optimization in Medical LVLMs |
提出细粒度偏好优化方法以解决医疗LVLM中的对齐问题 |
DPO direct preference optimization visual grounding |
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| 13 |
ReFree: Towards Realistic Co-Speech Video Generation via Reward-Free RL and Multilevel Speech Guidance |
提出ReFree-S2V以解决真实感对话视频生成问题 |
reinforcement learning flow matching character animation |
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| 14 |
Visual Place Recognition in Forests with Depth-Aware Distillation |
提出深度感知蒸馏框架以解决森林环境中的视觉地点识别问题 |
distillation |
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| 15 |
BSViT: A Burst Spiking Vision Transformer for Expressive and Efficient Visual Representation Learning |
提出BSViT以解决现有脉冲视觉变换器的效率与表现问题 |
representation learning |
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| 16 |
Objects Before Words: Object-First Inductive Biases for Grounding Language in Child-View Video |
提出BabyMind以解决儿童视角视频中的语言基础问题 |
contrastive learning egocentric |
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| 17 |
OR-Action: Multi-Role Video Understanding with Fine-Grained Actions |
提出OR-Action以解决手术室活动细粒度理解问题 |
distillation egocentric |
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| 18 |
MaskWAM: Unifying Mask Prompting and Prediction for World-Action Models |
提出MaskWAM以解决WAM中空间瓶颈问题 |
world action model world action models |
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| 19 |
ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding |
提出ReFoCUS以解决视频理解中的帧选择问题 |
reinforcement learning policy learning |
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| 20 |
RT-VLA: Real-Time Vision-Language-Action Models via Knowledge Distillation |
提出RT-VLA以解决实时视觉-语言-动作模型的延迟问题 |
distillation vision-language-action VLA |
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| 21 |
S$^2$COPE: Self-Supervised Concept Discovery via Preference Learning |
提出S$^2$COPE以解决自监督概念发现问题 |
preference learning representation learning |
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| 22 |
HumP-KD: A Hybrid Uncertainty-Aware Multi-Stage Progressive Knowledge Distillation Framework for Efficient Fire Classification |
提出HumP-KD框架以提高火灾分类的效率与准确性 |
distillation |
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| 23 |
SED:Lightweight Saliency prediction for Event-based data via Distillation |
提出SED以解决事件数据的轻量级显著性预测问题 |
distillation |
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| 24 |
ViT-Up: Faithful Feature Upsampling for Vision Transformers |
提出ViT-Up以解决视觉变换器特征上采样问题 |
representation learning depth estimation |
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| 25 |
FLaRA: Predicting Future Latent Representations for Accident Anticipation |
提出FLaRA以解决交通事故预测问题 |
Joint-Embedding Predictive Architecture joint-embedding predictive architecture |
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