3 citations · 5 across the 11 of their papers we have counts for
8 papers · 1 filter
Spatial-OPSD: Self-Improving Spatial Reasoning via Label-Free Self-Distillation
Zhenyu Liu, Zhangquan Chen, Keyi Chen +4
Vision-language models (VLMs) increasingly operate in embodied and spatially grounded settings, where accurate understanding of depth, viewpoint, and three-dimensional relations is…
MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality
Panqi Yang, Haodong Jing, Jiahao Chao +5
Unified visual tokenization faces a fundamental trade-off between high-fidelity pixel reconstruction (spatial equivariance) and semantic abstraction (conceptual invariance). We att…
This Looks Distinctly Like That: Grounding Interpretable Recognition in Stiefel Geometry against Neural Collapse
Junhao Jia, Jiaqi Wang, Yunyou Liu +4
Prototype networks provide an intrinsic case based explanation mechanism, but their interpretability is often undermined by prototype collapse, where multiple prototypes degenerate…
UniHOI: Unified Human-Object Interaction Understanding via Unified Token Space
Panqi Yang, Haodong Jing, Nanning Zheng +1
In the field of human-object interaction (HOI), detection and generation are two dual tasks that have traditionally been addressed separately, hindering the development of comprehe…
EVA: Mixture-of-Experts Semantic Variant Alignment for Compositional Zero-Shot Learning
Xiao Zhang, Yongqiang Ma, Haodong Jing +1
Compositional Zero-Shot Learning (CZSL) investigates compositional generalization capacity to recognize unknown state-object pairs based on learned primitive concepts. Existing CZS…
AttenST: A Training-Free Attention-Driven Style Transfer Framework with Pre-Trained Diffusion Models
Bo Huang, Wenlun Xu, Qizhuo Han +2
While diffusion models have achieved remarkable progress in style transfer tasks, existing methods typically rely on fine-tuning or optimizing pre-trained models during inference,…
See Through Their Minds: Learning Transferable Neural Representation from Cross-Subject fMRI
Yulong Liu, Yongqiang Ma, Guibo Zhu +2
Deciphering visual content from functional Magnetic Resonance Imaging (fMRI) helps illuminate the human vision system. However, the scarcity of fMRI data and noise hamper brain dec…
Complementing Onboard Sensors with Satellite Map: A New Perspective for HD Map Construction
Wenjie Gao, Jiawei Fu, Yanqing Shen +3
High-definition (HD) maps play a crucial role in autonomous driving systems. Recent methods have attempted to construct HD maps in real-time using vehicle onboard sensors. Due to t…