5 citations · 9 across the 11 of their papers we have counts for
12 papers
Distilling Image Prototypes for Guided Test-Time Adaptation
Liwen Wang, Xingbo Dong, Iman Yi Liao +4
Test-Time Adaptation (TTA) enhances the robustness of models against distribution shifts but faces two critical challenges: error accumulation from noisy pseudo-labels and catastro…
3D Scene-Adaptive Trajectory-Controllable Human Image Animation with Camera Movement
Deyin Liu, Jicheng Xu, Lin Yuanbo Wu +4
Human image animation, which aims to generate a video of a reference subject following a provided action sequence, has received increasing research interest. With the development o…
Beyond Consistency: Preserving Temporal Structure in Zero-Shot Video Editing
Deyin Liu, Yisheng Ding, Zhe Jin +3
Existing zero-shot video editing methods rely on pre-trained diffusion models, successfully achieving spatial control and basic temporal consistency but fundamentally fail to prese…
Unleashing Hierarchical Reasoning: An LLM-Driven Framework for Training-Free Referring Video Object Segmentation
Bingrui Zhao, Lin Yuanbo Wu, Xiangtian Fan +5
Referring Video Object Segmentation (RVOS) aims to segment an object of interest throughout a video based on a language description. The prominent challenge lies in aligning static…
Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization
Jingqi Wu, Hanxi Li, Lin Yuanbo Wu +3
Industrial product inspection is often performed using Anomaly Detection (AD) frameworks trained solely on non-defective samples. Although defective samples can be collected during…
Self-Navigated Residual Mamba for Universal Industrial Anomaly Detection
Hanxi Li, Jingqi Wu, Lin Yuanbo Wu +4
In this paper, we propose Self-Navigated Residual Mamba (SNARM), a novel framework for universal industrial anomaly detection that leverages ``self-referential learning'' within te…
A Deep Semantic Segmentation Network with Semantic and Contextual Refinements
Zhiyan Wang, Deyin Liu, Lin Yuanbo Wu +3
Semantic segmentation is a fundamental task in multimedia processing, which can be used for analyzing, understanding, editing contents of images and videos, among others. To accele…
Blended Latent Diffusion under Attention Control for Real-World Video Editing
Deyin Liu, Lin Yuanbo Wu, Xianghua Xie
Due to lack of fully publicly available text-to-video models, current video editing methods tend to build on pre-trained text-to-image generation models, however, they still face g…
Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization
Hanxi Li, Jingqi Wu, Lin Yuanbo Wu +3
In the realm of practical Anomaly Detection (AD) tasks, manual labeling of anomalous pixels proves to be a costly endeavor. Consequently, many AD methods are crafted as one-class c…
A Novel Approach to Industrial Defect Generation through Blended Latent Diffusion Model with Online Adaptation
Hanxi Li, Zhengxun Zhang, Hao Chen +4
Effectively addressing the challenge of industrial Anomaly Detection (AD) necessitates an ample supply of defective samples, a constraint often hindered by their scarcity in indust…
Industrial Anomaly Detection and Localization Using Weakly-Supervised Residual Transformers
Hanxi Li, Jingqi Wu, Deyin Liu +4
Recent advancements in industrial anomaly detection (AD) have demonstrated that incorporating a small number of anomalous samples during training can significantly enhance accuracy…
T-Person-GAN: Text-to-Person Image Generation with Identity-Consistency and Manifold Mix-Up
Deyin Liu, Lin Yuanbo Wu, Bo Li +1
In this paper, we present an end-to-end approach to generate high-resolution person images conditioned on texts only. State-of-the-art text-to-image generation models are mainly de…