3 citations · 7 across the 22 of their papers we have counts for
24 papers
DPA: Decoupling Product-Agnostic Anomaly Representations for Zero-shot Anomaly Generation
Hang Yao, Yansheng Fu, Ming Liu +4
Industrial anomaly detection benefits from anomaly samples, yet newly deployed products typically provide only normal images, making anomaly samples difficult to collect. Zero-shot…
Generalize LMMs to Versatile Visual Modalities via Fabricated Modality Synthesis
Shihao Yuan, Yuanze Li, Ruyi Zhang +2
Despite the advancements of Large Multimodal Models (LMMs) in RGB vision, their ability to generalize to unseen visual modalities remains a largely unexplored challenge. We argue t…
InstanceControl: Controllable Complex Image Generation without Instance Labeling
Xiaoyu Liu, Huan Wang, Fan Li +4
Controllable image generation methods, such as ControlNet, have demonstrated a remarkable capacity to introduce visual conditions(e.g., depth maps) to guide image generation. Howev…
OPERA: An Agent for Image Restoration with End-to-End Joint Planning-Execution Optimization
Feng Zhu, Shuyang Xie, Yihan Zeng +2
Real-world image restoration is challenging due to complex and interacting mixed degradations. Recent agent-based approaches address this problem by composing multiple task-specifi…
Traffic Sign Recognition in Autonomous Driving: Dataset, Benchmark, and Field Experiment
Guoyang Zhao, Weiqing Qi, Kai Zhang +7
Traffic Sign Recognition (TSR) is a core perception capability for autonomous driving, where robustness to cross-region variation, long-tailed categories, and semantic ambiguity is…
Cluster-Wise Spatio-Temporal Masking for Efficient Video-Language Pretraining
Weijun Zhuang, Yuqing Huang, Weikang Meng +5
Large-scale video-language pretraining enables strong generalization across multimodal tasks but often incurs prohibitive computational costs. Although recent advances in masked vi…
PreferThinker: Reasoning-based Personalized Image Preference Assessment
Shengqi Xu, Xinpeng Zhou, Yabo Zhang +6
Personalized image preference assessment aims to evaluate an individual user's image preferences by relying only on a small set of reference images as prior information. Existing m…
GLaVE-Cap: Global-Local Aligned Video Captioning with Vision Expert Integration
Wan Xu, Feng Zhu, Yihan Zeng +4
Video detailed captioning aims to generate comprehensive video descriptions to facilitate video understanding. Recently, most efforts in the video detailed captioning community hav…
MDIQA: Unified Image Quality Assessment for Multi-dimensional Evaluation and Restoration
Shunyu Yao, Ming Liu, Zhilu Zhang +4
Recent advancements in image quality assessment (IQA), driven by sophisticated deep neural network designs, have significantly improved the ability to approach human perceptions. H…
RefSTAR: Blind Facial Image Restoration with Reference Selection, Transfer, and Reconstruction
Zhicun Yin, Junjie Chen, Ming Liu +6
Blind facial image restoration is highly challenging due to unknown complex degradations and the sensitivity of humans to faces. Although existing methods introduce auxiliary infor…
Integrating Visual Interpretation and Linguistic Reasoning for Math Problem Solving
Zixian Guo, Ming Liu, Qilong Wang +4
Current large vision-language models (LVLMs) typically employ a connector module to link visual features with text embeddings of large language models (LLMs) and use end-to-end tra…
NTIRE 2025 Challenge on Real-World Face Restoration: Methods and Results
Zheng Chen, Jingkai Wang, Kai Liu +51
This paper provides a review of the NTIRE 2025 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes. The challenge focuses on ge…
Grounding-MD: Grounded Video-language Pre-training for Open-World Moment Detection
Weijun Zhuang, Qizhang Li, Xin Li +5
Temporal Action Detection and Moment Retrieval constitute two pivotal tasks in video understanding, focusing on precisely localizing temporal segments corresponding to specific act…
AnimateAnywhere: Rouse the Background in Human Image Animation
Xiaoyu Liu, Mingshuai Yao, Yabo Zhang +5
Human image animation aims to generate human videos of given characters and backgrounds that adhere to the desired pose sequence. However, existing methods focus more on human acti…
Beyond Static Scenes: Camera-controllable Background Generation for Human Motion
Mingshuai Yao, Mengting Chen, Qinye Zhou +9
In this paper, we investigate the generation of new video backgrounds given a human foreground video, a camera pose, and a reference scene image. This task presents three key chall…
Triad: Empowering LMM-based Anomaly Detection with Vision Expert-guided Visual Tokenizer and Manufacturing Process
Yuanze Li, Shihao Yuan, Haolin Wang +5
Although recent methods have tried to introduce large multimodal models (LMMs) into industrial anomaly detection (IAD), their generalization in the IAD field is far inferior to tha…
Personalized Image Generation with Deep Generative Models: A Decade Survey
Yuxiang Wei, Yiheng Zheng, Yabo Zhang +4
Recent advancements in generative models have significantly facilitated the development of personalized content creation. Given a small set of images with user-specific concept, pe…
Retrieval Augmented Image Harmonization
Haolin Wang, Ming Liu, Zifei Yan +3
When embedding objects (foreground) into images (background), considering the influence of photography conditions like illumination, it is usually necessary to perform image harmon…
Learning Spatially Decoupled Color Representations for Facial Image Colorization
Hangyan Zhu, Ming Liu, Chao Zhou +3
Image colorization methods have shown prominent performance on natural images. However, since humans are more sensitive to faces, existing methods are insufficient to meet the dema…
GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection
Hang Yao, Ming Liu, Haolin Wang +4
Diffusion models have shown superior performance on unsupervised anomaly detection tasks. Since trained with normal data only, diffusion models tend to reconstruct normal counterpa…
LLM as a Complementary Optimizer to Gradient Descent: A Case Study in Prompt Tuning
Zixian Guo, Ming Liu, Zhilong Ji +3
Mastering a skill generally relies on both hands-on experience from doers and insightful, high-level guidance by mentors. Will this strategy also work well for solving complex non-…
SmartControl: Enhancing ControlNet for Handling Rough Visual Conditions
Xiaoyu Liu, Yuxiang Wei, Ming Liu +4
Human visual imagination usually begins with analogies or rough sketches. For example, given an image with a girl playing guitar before a building, one may analogously imagine how…
Black-Box Tuning of Vision-Language Models with Effective Gradient Approximation
Zixian Guo, Yuxiang Wei, Ming Liu +4
Parameter-efficient fine-tuning (PEFT) methods have provided an effective way for adapting large vision-language models to specific tasks or scenarios. Typically, they learn a very…
Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly Detection
Yuanze Li, Haolin Wang, Shihao Yuan +6
Due to the training configuration, traditional industrial anomaly detection (IAD) methods have to train a specific model for each deployment scenario, which is insufficient to meet…