9 citations · 12 across the 33 of their papers we have counts for
18 papers · 1 filter
SPIN: Image Immunization Against Diffusion Editing via Single-Step Projection in Stochastic Neighborhoods
Fengming Gu, Jie Zhang, Zhongqi Wang +3
Diffusion models have greatly advanced instruction-guided image editing, while also raising concerns about unauthorized image manipulation. Image immunization addresses this risk b…
HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models
Feng He, Zhenting Wang, Qifan Wang +4
Hallucinations in vision language models (VLMs) are commonly treated as semantic errors, yet they often arise from partial or ambiguous visual evidence. Prior work mainly focuses o…
Dual-Adaptive SAM3: Hierarchical Routing over Low-Rank Expert Layers for Parameter-Efficient Medical Image Segmentation
Ying Chen, Jinyue Li, Kun Wang +2
The Segment Anything Model with Concepts (SAM3) heralds a new paradigm for open-vocabulary segmentation through natural language interaction, offering significant potential for med…
Synergistic Perception-Reasoning Governance: Grounding Medical MLLMs with Verifiable Anatomical Evidence
Rui Hao, Qiankun Li, Junyuan Mao +4
Multimodal large language models (MLLMs) show strong promise for clinical VQA and radiology report generation, yet inference-time hallucinations still undermine trustworthy use: mo…
Joint Medical Image Enhancement and Segmentation with Diffusion-based Symbiotic Information Interaction
Ying Chen, Jinyue Li, Qiankun Li
Image quality is critical for accurate medical diagnosis. However, MRI, CT, and ultrasound images are often of low resolution and quality due to cost constraints, complicating the…
M3Net: A Macro-to-Meso-to-Micro Clinical-inspired Hierarchical 3D Network for Pulmonary Nodule Classification
Jinyue Li, Yuzhou Yu, Jingjing Yang +7
The accurate classification of benign and malignant pulmonary nodules in CT scans is critical for early lung cancer screening, yet remains challenging due to the multi-scale and he…
Beyond Shortcuts: Mitigating Visual Illusions in Frozen VLMs via Qualitative Reasoning
Hao Guo, Fei Wang, Junjie Chen +4
While Vision-Language Models (VLMs) have achieved state-of-the-art performance in general visual tasks, their perceptual robustness remains remarkably brittle when confronted with…
Neural Network Optimization Reimagined: Decoupled Techniques for Scratch and Fine-Tuning
Xin Ning, Qiankun Li, Xiaolong Huang +5
With the accumulation of resources in the era of big data and the rise of pre-trained models in deep learning, optimizing neural networks for various tasks often involves different…
HG-Lane: High-Fidelity Generation of Lane Scenes under Adverse Weather and Lighting Conditions without Re-annotation
Daichao Zhao, Qiupu Chen, Feng He +2
Lane detection is a crucial task in autonomous driving, as it helps ensure the safe operation of vehicles. However, existing datasets such as CULane and TuSimple contain relatively…
Better Eyes, Better Thoughts: Why Vision Chain-of-Thought Fails in Medicine
Yuan Wu, Zongxian Yang, Jiayu Qian +5
Large vision-language models (VLMs) often benefit from chain-of-thought (CoT) prompting in general domains, yet its efficacy in medical vision-language tasks remains underexplored.…
Granulon: Awakening Pixel-Level Visual Encoders with Adaptive Multi-Granularity Semantics for MLLM
Junyuan Mao, Qiankun Li, Linghao Meng +5
Recent advances in multimodal large language models largely rely on CLIP-based visual encoders, which emphasize global semantic alignment but struggle with fine-grained visual unde…
Unleashing Foundation Vision Models: Adaptive Transfer for Diverse Data-Limited Scientific Domains
Qiankun Li, Feng He, Huabao Chen +3
In the big data era, the computer vision field benefits from large-scale datasets such as LAION-2B, LAION-400M, and ImageNet-21K, Kinetics, on which popular models like the ViT and…
OralGPT-Omni: A Versatile Dental Multimodal Large Language Model
Jing Hao, Yuci Liang, Lizhuo Lin +12
Multimodal Large Language Models (MLLMs) have exhibited immense potential across numerous medical specialties; yet, dentistry remains underexplored, in part due to limited domain-s…
Rethinking Facial Expression Recognition in the Era of Multimodal Large Language Models: Benchmark, Datasets, and Beyond
Fan Zhang, Haoxuan Li, Shengju Qian +9
Multimodal Large Language Models (MLLMs) have revolutionized numerous research fields, including computer vision and affective computing. As a pivotal challenge in this interdiscip…
From Pixels to Views: Learning Angular-Aware and Physics-Consistent Representations for Light Field Microscopy
Feng He, Guodong Tan, Qiankun Li +2
Light field microscopy (LFM) has become an emerging tool in neuroscience for large-scale neural imaging in vivo, notable for its single-exposure volumetric imaging, broad field of…
CircuitProbe: Tracing Visual Temporal Evidence Flow in Video Language Models
Yiming Zhang, Zhuokai Zhao, Chengzhang Yu +8
Autoregressive large vision--language models (LVLMs) interface video and language by projecting video features into the LLM's embedding space as continuous visual token embeddings.…
One Step Learning, One Step Review
Xiaolong Huang, Qiankun Li, Xueran Li +1
Visual fine-tuning has garnered significant attention with the rise of pre-trained vision models. The current prevailing method, full fine-tuning, suffers from the issue of knowled…
2nd Place Solution to Google Universal Image Embedding
Xiaolong Huang, Qiankun Li
Image representations are a critical building block of computer vision applications. This paper presents the 2nd place solution to the Google Universal Image Embedding Competition,…