37 citations · 41 across the 19 of their papers we have counts for
14 papers · 1 filter
StimFlow: Synthesizing Brain Activity from Images via Stimulus-conditioned Flow Matching
Bui Van Hung, Dang Thanh Vu, Hoang-Son Vo +3
The inherent variability of fMRI responses across trials encourages a generative view of the stimulus-to-response mapping. Prior generative encoders often operate in compressed lat…
TransNormal-2: Geometry-Grounded Rectified Flow with Edge-Aware Decoding for Precise Normal Estimation
Mingwei Li, Yi Yang, Hehe Fan
Diffusion-based models enable monocular geometry estimation, yet their pixel-space precision is limited by a shared, under-studied error source: VAE reconstruction degradation. The…
SmartMage: Dynamic Modality Orchestration for 3D Scene Understanding
Yue Zhang, Yingzhao Jian, Yunqiu Xu +2
Understanding 3D scenes is fundamental to embodied intelligence, requiring joint reasoning over heterogeneous information from multiple modalities, including visual and geometric c…
Depth Estimators Are Implicit Neural Fields for 3D Scene Geometry Inpainting and Reconstruction
Yingzhao Jian, Zihao Lin, Hehe Fan
The 3D geometry of real-world scene data is often incomplete. Mainstream methods use depth estimators to inpaint missing structure. However, their prediction results can be inconsi…
Skill-3D: Evolving Scene-Aware Skills for Agentic 3D Spatial Reasoning
Haoyuan Li, Zhengdong Hu, Jun Wang +2
This paper explores agentic 3D spatial understanding, i.e., MLLM agents performing 3D reasoning through tool use. Existing methods often misuse tools and exhibit biased tool prefer…
Stroke3D: Lifting 2D strokes into rigged 3D model via latent diffusion models
Ruisi Zhao, Haoren Zheng, Zongxin Yang +2
Rigged 3D assets are fundamental to 3D deformation and animation. However, existing 3D generation methods face challenges in generating animatable geometry, while rigging technique…
TransNormal: Dense Visual Semantics for Diffusion-based Transparent Object Normal Estimation
Mingwei Li, Hehe Fan, Yi Yang
Monocular normal estimation for transparent objects is critical for laboratory automation, yet it remains challenging due to complex light refraction and reflection. These optical…
DeMoGen: Towards Decompositional Human Motion Generation with Energy-Based Diffusion Models
Jianrong Zhang, Hehe Fan, Yi Yang
Human motions are compositional: complex behaviors can be described as combinations of simpler primitives. However, existing approaches primarily focus on forward modeling, e.g., l…
GraphTARIF: Linear Graph Transformer with Augmented Rank and Improved Focus
Zhaolin Hu, Kun Li, Hehe Fan +1
Linear attention mechanisms have emerged as efficient alternatives to full self-attention in Graph Transformers, offering linear time complexity. However, existing linear attention…
Text-Scene: A Scene-to-Language Parsing Framework for 3D Scene Understanding
Haoyuan Li, Rui Liu, Hehe Fan +1
Enabling agents to understand and interact with complex 3D scenes is a fundamental challenge for embodied artificial intelligence systems. While Multimodal Large Language Models (M…
Motion Matters: Motion-guided Modulation Network for Skeleton-based Micro-Action Recognition
Jihao Gu, Kun Li, Fei Wang +4
Micro-Actions (MAs) are an important form of non-verbal communication in social interactions, with potential applications in human emotional analysis. However, existing methods in…
BVINet: Unlocking Blind Video Inpainting with Zero Annotations
Zhiliang Wu, Kerui Chen, Kun Li +2
Video inpainting aims to fill in corrupted regions of the video with plausible contents. Existing methods generally assume that the locations of corrupted regions are known, focusi…
Prompt-Aware Controllable Shadow Removal
Kerui Chen, Zhiliang Wu, Wenjin Hou +3
Shadow removal aims to restore the image content in shadowed regions. While deep learning-based methods have shown promising results, they still face key challenges: 1) uncontrolle…
Prototypical Calibrating Ambiguous Samples for Micro-Action Recognition
Kun Li, Dan Guo, Guoliang Chen +5
Micro-Action Recognition (MAR) has gained increasing attention due to its crucial role as a form of non-verbal communication in social interactions, with promising potential for ap…