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Ruobing Zheng

7 accepted papers

2026

EchoMimicV3: 1.3B Parameters Are All You Need for Unified Multi-Modal and Multi-Task Human Animation

AAAI 2026technical

Recent work on human animation usually incorporates large-scale video models, thereby achieving more vivid performance. However, the practical use of such methods is hindered by the slow inference speed and high computational demands. Moreover, traditional work typically employs separate models for

Cited by 0SourcePDFScholar
2026

HumanSense: From Multimodal Perception to Empathetic Context-Aware Responses Through Reasoning MLLMs

AAAI 2026technical

While Multimodal Large Language Models (MLLMs) show immense promise for achieving truly human-like interactions, progress is hindered by the lack of fine-grained evaluation frameworks for human-centered scenarios, encompassing both the understanding of complex human intentions and the provision of e

Cited by 0SourcePDFScholar
2025

Animate-X: Universal Character Image Animation with Enhanced Motion Representation

ICLR 2025poster

Character image animation, which generates high-quality videos from a reference image and target pose sequence, has seen significant progress in recent years. However, most existing methods only apply to human figures, which usually do not generalize well on anthropomorphic characters commonly used…

Cited by 14SourcePDFScholar
2024

Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis

CVPR 2024poster

Recent works in implicit representations such as Neural Radiance Fields (NeRF) have advanced the generation of realistic and animatable head avatars from video sequences. These implicit methods are still confronted by visual artifacts and jitters since the lack of explicit geometric constraints pose…

2024

StyleTokenizer: Defining Image Style by a Single Instance for Controlling Diffusion Models

ECCV 2024poster

"Despite the burst of innovative methods for controlling the diffusion process, effectively controlling image styles in text-to-image generation remains a challenging task. Many adapter-based methods impose image representation conditions on the denoising process to accomplish image control. However…

2023

DC-Former: Diverse and Compact Transformer for Person Re-identification

AAAI 2023technical

In person re-identification (ReID) task, it is still challenging to learn discriminative representation by deep learning, due to limited data. Generally speaking, the model will get better performance when increasing the amount of data. The addition of similar classes strengthens the ability of the…