17 citations · 34 across the 8 of their papers we have counts for
9 papers
VOR-Bench: A Human Perception-Driven Benchmark for Video Object Removal
Haonan Huang, Tianrui Qiu, Xianghao Zang +10
Despite its crucial role in video object removal (VOR), existing evaluation paradigms face two critical limitations: questionable references and a misalignment between tradi- tiona…
Ripple: Real-Time Streaming Audio-Video Generation With Cross-Modal Recurrent Memory
Yanbo Ding, Zhizhi Guo, Quanyue Song +4
Audio-video generative models achieve impressive quality but suffer from high latency, making them unsuitable for real-time applications. Although several streaming audio-video gen…
OmniMate: Open-Ended Real-Time Streaming Audio-Visual Generation for Interactive Avatars
Quanyue Song, Yishan He, Yanbo Ding +4
Recent advances in diffusion-based generative models have enabled real-time audio-driven avatar generation and unified audio-visual synthesis, providing a promising foundation for…
InteractiveAvatar: Real-Time Streaming Video Generation for Consistent and Intent-Aware Avatars
Quanyue Song, Yishan He, Yanfei Zhang +6
Recent diffusion-based models have enabled realistic audio-driven avatar generation in real-time streaming. However, existing approaches struggle to maintain visual temporal consis…
Curriculum Group Policy Optimization: Adaptive Sampling for Unleashing the Potential of Text-to-Image Generation
Baoteng Li, Xianghao Zang, Xinran Wang +8
Text-to-Image (T2I) generation has achieved remarkable progress in recent years. Meanwhile, reinforcement learning methods, particularly those based on Group Relative Policy Optimi…
DataEvolver: Let Your Data Build and Improve Itself via Goal-Driven Loop Agents
Qisong Zhang, Wenzhuo Wu, Zhuangzhuang Jia +7
Constructing controllable visual data is a major bottleneck for image editing and multimodal understanding. Useful supervision is rarely produced by a single rendering pass; instea…
MTVCraft: Tokenizing 4D Motion for Arbitrary Character Animation
Yanbo Ding, Xirui Hu, Zhizhi Guo +6
Character image animation has rapidly advanced with the rise of digital humans. However, existing methods rely largely on 2D-rendered pose images for motion guidance, which limits…
Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data
Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +56
Synthetic data is gaining increasing popularity for face recognition technologies, mainly due to the privacy concerns and challenges associated with obtaining real data, including…
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +55
Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class v…