8 papers · 1 filter
Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models
Yuansen Liu, Haiming Tang, Jinlong Peng +12
Multimodal Large Language Models (MLLMs) have demonstrated significant advances in visual understanding tasks. However, their capacity to comprehend human-centric scenes has rarely…
Align and Surpass Human Camouflaged Perception: Visual Refocus Reinforcement Fine-Tuning
Ruolin Shen, Xiaozhong Ji, Kai WU +5
Current multi-modal models exhibit a notable misalignment with the human visual system when identifying objects that are visually assimilated into the background. Our observations…
Disentangle Identity, Cooperate Emotion: Correlation-Aware Emotional Talking Portrait Generation
Weipeng Tan, Chuming Lin, Chengming Xu +6
Recent advances in Talking Head Generation (THG) have achieved impressive lip synchronization and visual quality through diffusion models; yet existing methods struggle to generate…
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…
SVP: Style-Enhanced Vivid Portrait Talking Head Diffusion Model
Weipeng Tan, Chuming Lin, Chengming Xu +5
Talking Head Generation (THG), typically driven by audio, is an important and challenging task with broad application prospects in various fields such as digital humans, film produ…
RealTalk: Real-time and Realistic Audio-driven Face Generation with 3D Facial Prior-guided Identity Alignment Network
Xiaozhong Ji, Chuming Lin, Zhonggan Ding +6
Person-generic audio-driven face generation is a challenging task in computer vision. Previous methods have achieved remarkable progress in audio-visual synchronization, but there…
DiffuMatting: Synthesizing Arbitrary Objects with Matting-level Annotation
Xiaobin Hu, Xu Peng, Donghao Luo +7
Due to the difficulty and labor-consuming nature of getting highly accurate or matting annotations, there only exists a limited amount of highly accurate labels available to the pu…
UniM-OV3D: Uni-Modality Open-Vocabulary 3D Scene Understanding with Fine-Grained Feature Representation
Qingdong He, Jinlong Peng, Zhengkai Jiang +7
3D open-vocabulary scene understanding aims to recognize arbitrary novel categories beyond the base label space. However, existing works not only fail to fully utilize all the avai…