9 citations · 21 across the 28 of their papers we have counts for
24 papers · 1 filter
TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioning
Zijing Qin, Jun Zhou, Ruicheng Zhang +5
Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce. However, existing methods primarily focus on low-r…
SignGPT: Toward LLM-Mediated Sign Language Interaction through Gloss-Free Translation and Generation
Ronghui Li, Jun Dong, Zhongyuan Hu +8
Large language models (LLMs) provide limited support for sign language interaction. Unifying sign language translation (SLT) and generation (SLG) to enable sign language as both in…
KVPO: ODE-Native GRPO for Autoregressive Video Alignment via KV Semantic Exploration
Ruicheng Zhang, Kaixi Cong, Jun Zhou +5
Aligning streaming autoregressive (AR) video generators with human preferences is challenging. Existing reinforcement learning methods predominantly rely on noise-based exploration…
RoboStereo: Dual-Tower 4D Embodied World Models for Unified Policy Optimization
Ruicheng Zhang, Guangyu Chen, Zunnan Xu +5
Scalable Embodied AI faces fundamental constraints due to prohibitive costs and safety risks of real-world interaction. While Embodied World Models (EWMs) offer promise through ima…
Identity-Consistent Video Generation under Large Facial-Angle Variations
Bin Hu, Zipeng Qi, Guoxi Huang +6
Single-view reference-to-video methods often struggle to preserve identity consistency under large facial-angle variations. This limitation naturally motivates the incorporation of…
Zo3T: Zero-Shot 3D-Aware Trajectory-Guided Image-to-Video Generation via Test-Time Training
Ruicheng Zhang, Jun Zhou, Zunnan Xu +5
Trajectory-Guided image-to-video (I2V) generation aims to synthesize videos that adhere to user-specified motion instructions. Existing methods typically rely on computationally ex…
HaploOmni: Unified Single Transformer for Multimodal Video Understanding and Generation
Yicheng Xiao, Lin Song, Rui Yang +6
With the advancement of language models, unified multimodal understanding and generation have made significant strides, with model architectures evolving from separated components…
SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learning
Jiaqi Huang, Zunnan Xu, Jun Zhou +6
Leveraging multimodal large models for image segmentation has become a prominent research direction. However, existing approaches typically rely heavily on manually annotated datas…
Audio-visual Controlled Video Diffusion with Masked Selective State Spaces Modeling for Natural Talking Head Generation
Fa-Ting Hong, Zunnan Xu, Zixiang Zhou +5
Talking head synthesis is vital for virtual avatars and human-computer interaction. However, most existing methods are typically limited to accepting control from a single primary…
InterAnimate: Taming Region-aware Diffusion Model for Realistic Human Interaction Animation
Yukang Lin, Yan Hong, Zunnan Xu +10
Recent video generation research has focused heavily on isolated actions, leaving interactive motions-such as hand-face interactions-largely unexamined. These interactions are esse…
FireEdit: Fine-grained Instruction-based Image Editing via Region-aware Vision Language Model
Jun Zhou, Jiahao Li, Zunnan Xu +6
Currently, instruction-based image editing methods have made significant progress by leveraging the powerful cross-modal understanding capabilities of vision language models (VLMs)…
HunyuanPortrait: Implicit Condition Control for Enhanced Portrait Animation
Zunnan Xu, Zhentao Yu, Zixiang Zhou +10
We introduce HunyuanPortrait, a diffusion-based condition control method that employs implicit representations for highly controllable and lifelike portrait animation. Given a sing…
Densely Connected Parameter-Efficient Tuning for Referring Image Segmentation
Jiaqi Huang, Zunnan Xu, Ting Liu +4
In the domain of computer vision, Parameter-Efficient Tuning (PET) is increasingly replacing the traditional paradigm of pre-training followed by full fine-tuning. PET is particula…
HunyuanVideo: A Systematic Framework For Large Video Generative Models
Weijie Kong, Qi Tian, Zijian Zhang +49
Recent advancements in video generation have significantly impacted daily life for both individuals and industries. However, the leading video generation models remain closed-sourc…
AToM: Aligning Text-to-Motion Model at Event-Level with GPT-4Vision Reward
Haonan Han, Xiangzuo Wu, Huan Liao +5
Recently, text-to-motion models have opened new possibilities for creating realistic human motion with greater efficiency and flexibility. However, aligning motion generation with…
MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression Comprehension
Ting Liu, Zunnan Xu, Yue Hu +3
Referring Expression Comprehension (REC), which aims to ground a local visual region via natural language, is a task that heavily relies on multimodal alignment. Most existing meth…
Alignment is All You Need: A Training-free Augmentation Strategy for Pose-guided Video Generation
Xiaoyu Jin, Zunnan Xu, Mingwen Ou +1
Character animation is a transformative field in computer graphics and vision, enabling dynamic and realistic video animations from static images. Despite advancements, maintaining…
V3Det Challenge 2024 on Vast Vocabulary and Open Vocabulary Object Detection: Methods and Results
Jiaqi Wang, Yuhang Zang, Pan Zhang +31
Detecting objects in real-world scenes is a complex task due to various challenges, including the vast range of object categories, and potential encounters with previously unknown…
REPARO: Compositional 3D Assets Generation with Differentiable 3D Layout Alignment
Haonan Han, Rui Yang, Huan Liao +6
Traditional image-to-3D models often struggle with scenes containing multiple objects due to biases and occlusion complexities. To address this challenge, we present REPARO, a nove…
Sparse-Tuning: Adapting Vision Transformers with Efficient Fine-tuning and Inference
Ting Liu, Xuyang Liu, Liangtao Shi +6
Parameter-efficient fine-tuning (PEFT) has emerged as a popular solution for adapting pre-trained Vision Transformer (ViT) models to downstream applications by updating only a smal…
MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models
Zunnan Xu, Yukang Lin, Haonan Han +4
Gesture synthesis is a vital realm of human-computer interaction, with wide-ranging applications across various fields like film, robotics, and virtual reality. Recent advancements…
Chain of Generation: Multi-Modal Gesture Synthesis via Cascaded Conditional Control
Zunnan Xu, Yachao Zhang, Sicheng Yang +2
This study aims to improve the generation of 3D gestures by utilizing multimodal information from human speech. Previous studies have focused on incorporating additional modalities…
Consistent123: One Image to Highly Consistent 3D Asset Using Case-Aware Diffusion Priors
Yukang Lin, Haonan Han, Chaoqun Gong +3
Reconstructing 3D objects from a single image guided by pretrained diffusion models has demonstrated promising outcomes. However, due to utilizing the case-agnostic rigid strategy,…
Bridging Vision and Language Encoders: Parameter-Efficient Tuning for Referring Image Segmentation
Zunnan Xu, Zhihong Chen, Yong Zhang +3
Parameter Efficient Tuning (PET) has gained attention for reducing the number of parameters while maintaining performance and providing better hardware resource savings, but few st…