1 citations · 1 across the 7 of their papers we have counts for
7 papers
Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection
Yuhu Bai, Jiangning Zhang, Yunkang Cao +4
With the advent of vision-language models (e.g., CLIP) in zero- and few-shot settings, CLIP has been widely applied to zero-shot anomaly detection (ZSAD) in recent research, where…
UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
Zhucun Xue, Jiangning Zhang, Teng Hu +8
The quality of the video dataset (image quality, resolution, and fine-grained caption) greatly influences the performance of the video generation model. The growing demand for vide…
AdaVideoRAG: Omni-Contextual Adaptive Retrieval-Augmented Efficient Long Video Understanding
Zhucun Xue, Jiangning Zhang, Xurong Xie +4
Multimodal Large Language Models (MLLMs) perform well in video understanding but degrade on long videos due to fixed-length context and weak long-term dependency modeling. Retrieva…
UMC: Unified Resilient Controller for Legged Robots with Joint Malfunctions
Yu Qiu, Xin Lin, Jingbo Wang +3
Adaptation to unpredictable damages is crucial for autonomous legged robots, yet existing methods based on multi-policy or meta-learning frameworks face challenges like limited gen…
EMOv2: Pushing 5M Vision Model Frontier
Jiangning Zhang, Teng Hu, Haoyang He +6
This work focuses on developing parameter-efficient and lightweight models for dense predictions while trading off parameters, FLOPs, and performance. Our goal is to set up the new…
DynamicControl: Adaptive Condition Selection for Improved Text-to-Image Generation
Qingdong He, Jinlong Peng, Pengcheng Xu +8
To enhance the controllability of text-to-image diffusion models, current ControlNet-like models have explored various control signals to dictate image attributes. However, existin…
MIMAFace: Face Animation via Motion-Identity Modulated Appearance Feature Learning
Yue Han, Junwei Zhu, Yuxiang Feng +5
Current diffusion-based face animation methods generally adopt a ReferenceNet (a copy of U-Net) and a large amount of curated self-acquired data to learn appearance features, as ro…