9 citations · 17 across the 12 of their papers we have counts for
12 papers
GaussianDS: Depth-supervised Semantic Gaussian Splatting for Scene Understanding
Yufei Zhang, Chenlu Zhan, Hongwei Wang
3D Gaussian Splatting provides an efficient representation for 3D reconstruction, and recent extensions attach semantic attributes to Gaussians for open-vocabulary scene understand…
When Visual Signals Mislead: A Mechanistic Study of Attribute Hallucination in Vision-Language Models
Yufei Zhang, Chenlu Zhan, Hongwei Wang
Attribute hallucination---where vision-language models (VLMs) correctly identify an object but mischaracterize its properties---is prevalent yet mechanistically poorly understood.…
SpatialAfford: Teaching Compact VLMs Where to Look and Where to Ground for Affordance
Yufei Zhang, Chenlu Zhan, Donghui Sun +2
Affordance grounding aims to localize the functional region for interaction, such as the handle to grasp or the button to press, rather than the whole object. This makes it more ch…
SAD-GS: Learning Reliable 3D Semantic Gaussian Fields via Dynamic Geo-Semantic Anchoring
Yufei Zhang, Chenlu Zhan, Gaoang Wang +1
Open-vocabulary 3D semantic Gaussian field learning relies on multi-view 2D supervision, whose semantic targets and spatial assignments are often unreliable. Across varying viewpoi…
FreeQ-Graph: Free-form Querying with Semantic Consistent Scene Graph for 3D Scene Understanding
Chenlu Zhan, Yufei Zhang, Gaoang Wang +1
Semantic querying in complex 3D scenes through free-form language presents a significant challenge. Existing 3D scene understanding methods use large-scale training data and CLIP t…
Hi-LSplat: Hierarchical 3D Language Gaussian Splatting
Chenlu Zhan, Yufei Zhang, Gaoang Wang +1
Modeling 3D language fields with Gaussian Splatting for open-ended language queries has recently garnered increasing attention. However, recent 3DGS-based models leverage view-depe…
RDG-GS: Relative Depth Guidance with Gaussian Splatting for Real-time Sparse-View 3D Rendering
Chenlu Zhan, Yufei Zhang, Yu Lin +2
Efficiently synthesizing novel views from sparse inputs while maintaining accuracy remains a critical challenge in 3D reconstruction. While advanced techniques like radiance fields…
Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents
Hanrong Zhang, Jingyuan Huang, Kai Mei +5
Although LLM-based agents, powered by Large Language Models (LLMs), can use external tools and memory mechanisms to solve complex real-world tasks, they may also introduce critical…
Invisible Backdoor Attack against Self-supervised Learning
Hanrong Zhang, Zhenting Wang, Boheng Li +7
Self-supervised learning (SSL) models are vulnerable to backdoor attacks. Existing backdoor attacks that are effective in SSL often involve noticeable triggers, like colored patche…
MedM2G: Unifying Medical Multi-Modal Generation via Cross-Guided Diffusion with Visual Invariant
Chenlu Zhan, Yu Lin, Gaoang Wang +2
Medical generative models, acknowledged for their high-quality sample generation ability, have accelerated the fast growth of medical applications. However, recent works concentrat…
UniDCP: Unifying Multiple Medical Vision-language Tasks via Dynamic Cross-modal Learnable Prompts
Chenlu Zhan, Yufei Zhang, Yu Lin +2
Medical vision-language pre-training (Med-VLP) models have recently accelerated the fast-growing medical diagnostics application. However, most Med-VLP models learn task-specific r…
UnICLAM:Contrastive Representation Learning with Adversarial Masking for Unified and Interpretable Medical Vision Question Answering
Chenlu Zhan, Peng Peng, Hongsen Wang +2
Medical Visual Question Answering (Medical-VQA) aims to to answer clinical questions regarding radiology images, assisting doctors with decision-making options. Nevertheless, curre…