36 citations · 84 across the 65 of their papers we have counts for
73 papers
GSHeadRelight: Fast Relightability for 3D Gaussian Head Synthesis
Henglei Lv, Bailin Deng, Jianzhu Guo +4
Relighting and novel view synthesis of human portraits are essential in applications such as portrait photography, virtual reality (VR), and augmented reality (AR). Despite recent…
HandsOnWorld: Unconstrained Egocentric Video Generation with Camera-Disentangled Hand Control
Yushuo Chen, Xiaoyu Shi, Xiaoshi Wu +3
We present HandsOnWorld, a framework for hand-controlled egocentric video generation that learns directly from unconstrained monocular video. Prior generators depend on 3D hand ann…
Amortized Moment Matching for Visual Generation
Wenze Liu, Xintao Wang, Pengfei Wan +1
We propose amortized moment matching, utilizing neural networks to learn data moments as distributional training signals. By casting diffusion denoisers through polynomial projecti…
MAVIN: Multi-Shot Audio-Visual Generation with Customized Narrative Control
Kaiqi Liu, Yunyao Mao, Ziqi Cai +8
While recent generative models produce high-fidelity videos, they struggle with the complex narrative control required for coherent multi-shot audio-visual generation. Existing met…
AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization
Yu Li, Menghan Xia, Gongye Liu +8
Despite being a pivotal frontier, interactive world modeling remains underexplored in terms of the versatile controllability required by practical scenarios. To bridge this gap, we…
CineScene: Implicit 3D as Effective Scene Representation for Cinematic Video Generation
Kaiyi Huang, Yukun Huang, Yu Li +8
Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical se…
GARDO: Reinforcing Diffusion Models without Reward Hacking
Haoran He, Yuxiao Ye, Jie Liu +7
Fine-tuning diffusion models via online reinforcement learning (RL) has shown great potential for enhancing text-to-image alignment. However, since precisely specifying a ground-tr…
SVG-T2I: Scaling Up Text-to-Image Latent Diffusion Model Without Variational Autoencoder
Minglei Shi, Haolin Wang, Borui Zhang +11
Visual generation grounded in Visual Foundation Model (VFM) representations offers a highly promising unified pathway for integrating visual understanding, perception, and generati…
FilmWeaver: Weaving Consistent Multi-Shot Videos with Cache-Guided Autoregressive Diffusion
Xiangyang Luo, Qingyu Li, Xiaokun Liu +7
Current video generation models perform well at single-shot synthesis but struggle with multi-shot videos, facing critical challenges in maintaining character and background consis…
MultiShotMaster: A Controllable Multi-Shot Video Generation Framework
Qinghe Wang, Xiaoyu Shi, Baolu Li +7
Current video generation techniques excel at single-shot clips but struggle to produce narrative multi-shot videos, which require flexible shot arrangement, coherent narrative, and…
VidEmo: Affective-Tree Reasoning for Emotion-Centric Video Foundation Models
Zhicheng Zhang, Weicheng Wang, Yongjie Zhu +4
Understanding and predicting emotion from videos has gathered significant attention in recent studies, driven by advancements in video large language models (VideoLLMs). While adva…
GRPO-Guard: Mitigating Implicit Over-Optimization in Flow Matching via Regulated Clipping
Jing Wang, Jiajun Liang, Jie Liu +10
Recently, GRPO-based reinforcement learning has shown remarkable progress in optimizing flow-matching models, effectively improving their alignment with task-specific rewards. With…
VFXMaster: Unlocking Dynamic Visual Effect Generation via In-Context Learning
Baolu Li, Yiming Zhang, Qinghe Wang +8
Visual effects (VFX) are crucial to the expressive power of digital media, yet their creation remains a major challenge for generative AI. Prevailing methods often rely on the one-…
UniMMVSR: A Unified Multi-Modal Framework for Cascaded Video Super-Resolution
Shian Du, Menghan Xia, Chang Liu +4
Cascaded video super-resolution has emerged as a promising technique for decoupling the computational burden associated with generating high-resolution videos using large foundatio…
OmniX: From Unified Panoramic Generation and Perception to Graphics-Ready 3D Scenes
Yukun Huang, Jiwen Yu, Yanning Zhou +4
There are two prevalent ways for automatic 3D scene construction: procedural generation and 2D lifting. Among these, panorama-based 2D lifting has emerged as a promising technique,…
Latent Diffusion Model without Variational Autoencoder
Minglei Shi, Haolin Wang, Wenzhao Zheng +6
Recent progress in diffusion-based visual generation has largely relied on latent diffusion models with variational autoencoders (VAEs). While effective for high-fidelity synthesis…
VideoCanvas: Unified Video Completion from Arbitrary Spatiotemporal Patches via In-Context Conditioning
Minghong Cai, Qiulin Wang, Zongli Ye +7
Existing controllable video generation methods are typically designed for rigid, task-specific settings, such as first-frame image-to-video, inpainting, or interpolation, treating…
UniVideo: Unified Understanding, Generation, and Editing for Videos
Cong Wei, Quande Liu, Zixuan Ye +5
Unified multimodal models have shown promising results in multimodal content generation and editing but remain largely limited to the image domain. In this work, we present UniVide…
PatchVSR: Breaking Video Diffusion Resolution Limits with Patch-wise Video Super-Resolution
Shian Du, Menghan Xia, Chang Liu +5
Pre-trained video generation models hold great potential for generative video super-resolution (VSR). However, adapting them for full-size VSR, as most existing methods do, suffers…
Score Augmentation for Diffusion Models
Liang Hou, Yuan Gao, Boyuan Jiang +6
Diffusion models have achieved remarkable success in generative modeling. However, this study confirms the existence of overfitting in diffusion model training, particularly in dat…
GGTalker: Talking Head Systhesis with Generalizable Gaussian Priors and Identity-Specific Adaptation
Wentao Hu, Shunkai Li, Ziqiao Peng +6
Creating high-quality, generalizable speech-driven 3D talking heads remains a persistent challenge. Previous methods achieve satisfactory results for fixed viewpoints and small-sca…
MODA: MOdular Duplex Attention for Multimodal Perception, Cognition, and Emotion Understanding
Zhicheng Zhang, Wuyou Xia, Chenxi Zhao +7
Multimodal large language models (MLLMs) recently showed strong capacity in integrating data among multiple modalities, empowered by a generalizable attention architecture. Advance…
Imbalance in Balance: Online Concept Balancing in Generation Models
Yukai Shi, Jiarong Ou, Rui Chen +6
In visual generation tasks, the responses and combinations of complex concepts often lack stability and are error-prone, which remains an under-explored area. In this paper, we att…
VMoBA: Mixture-of-Block Attention for Video Diffusion Models
Jianzong Wu, Liang Hou, Haotian Yang +5
The quadratic complexity of full attention mechanisms poses a significant bottleneck for Video Diffusion Models (VDMs) aiming to generate long-duration, high-resolution videos. Whi…