9 papers · 1 filter
Geometrically Constrained Stenosis Editing in Coronary Angiography via Entropic Optimal Transport
Jialin Li, Zhuo Zhang, Yue Cao +4
The scarcity of high-quality imaging data for coronary angiography (CAG) stenosis limits the clinical translation of automated stenosis detection. Synthetic stenosis data provides…
Improving Human Image Animation via Semantic Representation Alignment
Chang Liu, Mengting Chen, Yixuan Huang +5
The field of image-to-video generation has made remarkable progress. However, challenges such as human limb twisting and facial distortion persist, especially when generating long…
Wave-Particle (Continuous-Discrete) Dualistic Visual Tokenization for Unified Understanding and Generation
Yizhu Chen, Chen Ju, Zhicheng Wang +5
The unification of understanding and generation within a single multi-modal large model (MLLM) remains one significant challenge, largely due to the dichotomy between continuous an…
Contrast-Unity for Partially-Supervised Temporal Sentence Grounding
Haicheng Wang, Chen Ju, Weixiong Lin +4
Temporal sentence grounding aims to detect event timestamps described by the natural language query from given untrimmed videos. The existing fully-supervised setting achieves grea…
Advancing Myopia To Holism: Fully Contrastive Language-Image Pre-training
Haicheng Wang, Chen Ju, Weixiong Lin +9
In rapidly evolving field of vision-language models (VLMs), contrastive language-image pre-training (CLIP) has made significant strides, becoming foundation for various downstream…
Turbo: Informativity-Driven Acceleration Plug-In for Vision-Language Large Models
Chen Ju, Haicheng Wang, Haozhe Cheng +6
Vision-Language Large Models (VLMs) recently become primary backbone of AI, due to the impressive performance. However, their expensive computation costs, i.e., throughput and dela…
Tunnel Try-on: Excavating Spatial-temporal Tunnels for High-quality Virtual Try-on in Videos
Zhengze Xu, Mengting Chen, Zhao Wang +6
Video try-on is a challenging task and has not been well tackled in previous works. The main obstacle lies in preserving the details of the clothing and modeling the coherent motio…
Cell Variational Information Bottleneck Network
Zhonghua Zhai, Chen Ju, Jinsong Lan +1
In this work, we propose Cell Variational Information Bottleneck Network (cellVIB), a convolutional neural network using information bottleneck mechanism, which can be combined wit…
Wear-Any-Way: Manipulable Virtual Try-on via Sparse Correspondence Alignment
Mengting Chen, Xi Chen, Zhonghua Zhai +4
This paper introduces a novel framework for virtual try-on, termed Wear-Any-Way. Different from previous methods, Wear-Any-Way is a customizable solution. Besides generating high-f…