4 citations · 5 across the 6 of their papers we have counts for
6 papers · 1 filter
Knowledge is Power: Advancing Few-shot Action Recognition with Multimodal Semantics from MLLMs
Jiazheng Xing, Chao Xu, Hangjie Yuan +4
Multimodal Large Language Models (MLLMs) have propelled the field of few-shot action recognition (FSAR). However, preliminary explorations in this area primarily focus on generatin…
High-fidelity Generalized Emotional Talking Face Generation with Multi-modal Emotion Space Learning
Chao Xu, Junwei Zhu, Jiangning Zhang +6
Recently, emotional talking face generation has received considerable attention. However, existing methods only adopt one-hot coding, image, or audio as emotion conditions, thus la…
Multimodal-driven Talking Face Generation via a Unified Diffusion-based Generator
Chao Xu, Shaoting Zhu, Junwei Zhu +4
Multimodal-driven talking face generation refers to animating a portrait with the given pose, expression, and gaze transferred from the driving image and video, or estimated from t…
Better "CMOS" Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-Resolution
Xuhai Chen, Jiangning Zhang, Chao Xu +3
Most of the existing blind image Super-Resolution (SR) methods assume that the blur kernels are space-invariant. However, the blur involved in real applications are usually space-v…
Region-Aware Face Swapping
Chao Xu, Jiangning Zhang, Miao Hua +3
This paper presents a novel Region-Aware Face Swapping (RAFSwap) network to achieve identity-consistent harmonious high-resolution face generation in a local-global manner: \textbf…
SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution
Jiangning Zhang, Chao Xu, Jian Li +4
In the practical application of restoring low-resolution gray-scale images, we generally need to run three separate processes of image colorization, super-resolution, and dows-samp…