3 citations · 4 across the 12 of their papers we have counts for
12 papers
Skill Training with Corruption and Reconstruction Loop
Mo Li, Zixin Yin, Ting Cao +3
Large Language Models (LLMs) often struggle in highly specialized domains. Rather than parameter-level adaptation of LLMs which is costly and difficult to interpret, external skill…
Motion4Motion: Motion Transfer Across Subjects at Inference
Ling-Hao Chen, Zixin Yin, Duomin Wang +2
This work explores the motion transfer from one video to another, which is crucial in animation for diverse characters. Previously, video motion transfer has been largely explored…
SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
Haiwen Diao, Penghao Wu, Hanming Deng +55
Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…
ReasonEdit: Towards Reasoning-Enhanced Image Editing Models
Fukun Yin, Shiyu Liu, Yucheng Han +12
Recent advances in image editing models have shown remarkable progress. A common architectural design couples a multimodal large language model (MLLM) encoder with a diffusion deco…
ConsistEdit: Highly Consistent and Precise Training-free Visual Editing
Zixin Yin, Ling-Hao Chen, Lionel Ni +1
Recent advances in training-free attention control methods have enabled flexible and efficient text-guided editing capabilities for existing generation models. However, current app…
UniVerse-1: Unified Audio-Video Generation via Stitching of Experts
Duomin Wang, Wei Zuo, Aojie Li +7
We introduce UniVerse-1, a unified, Veo-3-like model capable of simultaneously generating coordinated audio and video. To enhance training efficiency, we bypass training from scrat…
LazyDrag: Enabling Stable Drag-Based Editing on Multi-Modal Diffusion Transformers via Explicit Correspondence
Zixin Yin, Xili Dai, Duomin Wang +4
The reliance on implicit point matching via attention has become a core bottleneck in drag-based editing, resulting in a fundamental compromise on weakened inversion strength and c…
Motion2Motion: Cross-topology Motion Transfer with Sparse Correspondence
Ling-Hao Chen, Yuhong Zhang, Zixin Yin +5
This work studies the challenge of transfer animations between characters whose skeletal topologies differ substantially. While many techniques have advanced retargeting techniques…
Training-Free Text-Guided Color Editing with Multi-Modal Diffusion Transformer
Zixin Yin, Xili Dai, Ling-Hao Chen +7
Text-guided color editing in images and videos is a fundamental yet unsolved problem, requiring fine-grained manipulation of color attributes, including albedo, light source color,…
SpeakerVid-5M: A Large-Scale High-Quality Dataset for Audio-Visual Dyadic Interactive Human Generation
Youliang Zhang, Zhaoyang Li, Duomin Wang +6
The rapid development of large-scale models has catalyzed significant breakthroughs in the digital human domain. These advanced methodologies offer high-fidelity solutions for avat…
Talking Head Generation with Probabilistic Audio-to-Visual Diffusion Priors
Zhentao Yu, Zixin Yin, Deyu Zhou +3
In this paper, we introduce a simple and novel framework for one-shot audio-driven talking head generation. Unlike prior works that require additional driving sources for controlle…
Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesis
Duomin Wang, Yu Deng, Zixin Yin +2
We present a novel one-shot talking head synthesis method that achieves disentangled and fine-grained control over lip motion, eye gaze&blink, head pose, and emotional expression.…