6 citations · 12 across the 22 of their papers we have counts for
24 papers · 1 filter
AffineTok: Semantic Affine Consistency for Diffusion-Friendly Visual Tokenizer
Junqiu Yu, Pandeng Li, Yikai Wang +11
Visual tokenizers increasingly inject semantic supervision into latent spaces to make downstream diffusion easier. Yet how these semantics should be organized to facilitate denoisi…
RefCaptioner: Multi-Reference Image-Grounded Video Captioning
Tengfei Liu, Yang Shi, Yuran Wang +16
Existing video captioning models generate natural descriptions of video content but cannot explicitly ground local visual elements to multiple reference images. We introduce multi-…
KeyFrame-Compass: Towards Comprehensive Evaluation of Keyframe-Conditioned Video Generation
Yuqi Tang, Tengfei Liu, Yizheng Lai +18
Video generation increasingly relies on keyframe-based workflows, where creators specify a sequence of reference images to guide generation. Although recent models support multi-ke…
Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models
Jiazheng Xing, Hangjie Yuan, Lingling Cai +9
Connector-based video unified models have demonstrated strong capability in instruction-grounded video synthesis, but integrating a large high-fidelity generator into the unified t…
MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation
Yujie Wei, Yujin Han, Zhekai Chen +20
Video generation is rapidly evolving from single-shot synthesis to complex multi-shot audio-video (MSAV) narratives to meet real-world demands. However, evaluating such frontier mo…
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos
Yuqi Tang, Yang Shi, Zhuoran Zhang +21
Recent video generative models have greatly improved the realism of AI-generated videos, yet their outputs still exhibit artifacts such as temporal inconsistencies, structural dist…
Bridging Brain and Semantics: A Hierarchical Framework for Semantically Enhanced fMRI-to-Video Reconstruction
Yujie Wei, Chenglong Ma, Jianxiong Gao +6
Reconstructing dynamic visual experiences as videos from functional magnetic resonance imaging (fMRI) is pivotal for advancing the understanding of neural processes. However, curre…
AesRM: Improving Video Aesthetics with Expert-Level Feedback
Yujin Han, Yujie Wei, Yefei He +7
Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors and cinematic lighting, beyo…
AIBench: Evaluating Visual-Logical Consistency in Academic Illustration Generation
Zhaohe Liao, Kaixun Jiang, Zhihang Liu +11
Although image generation has boosted various applications via its rapid evolution, whether the state-of-the-art models are able to produce ready-to-use academic illustrations for…
Towards Reason-Informed Video Editing in Unified Models with Self-Reflective Learning
Xinyu Liu, Hangjie Yuan, Yujie Wei +9
Unified video models exhibit strong capabilities in understanding and generation, yet they struggle with reason-informed visual editing even when equipped with powerful internal vi…
Routing Matters in MoE: Scaling Diffusion Transformers with Explicit Routing Guidance
Yujie Wei, Shiwei Zhang, Hangjie Yuan +8
Mixture-of-Experts (MoE) has emerged as a powerful paradigm for scaling model capacity while preserving computational efficiency. Despite its notable success in large language mode…
TTS-VAR: A Test-Time Scaling Framework for Visual Auto-Regressive Generation
Zhekai Chen, Ruihang Chu, Yukang Chen +4
Scaling visual generation models is essential for real-world content creation, yet requires substantial training and computational expenses. Alternatively, test-time scaling has ga…
SynMotion: Semantic-Visual Adaptation for Motion Customized Video Generation
Shuai Tan, Biao Gong, Yujie Wei +8
Diffusion-based video motion customization facilitates the acquisition of human motion representations from a few video samples, while achieving arbitrary subjects transfer through…
Taming Consistency Distillation for Accelerated Human Image Animation
Xiang Wang, Shiwei Zhang, Hangjie Yuan +5
Recent advancements in human image animation have been propelled by video diffusion models, yet their reliance on numerous iterative denoising steps results in high inference costs…
DreamRelation: Relation-Centric Video Customization
Yujie Wei, Shiwei Zhang, Hangjie Yuan +8
Relational video customization refers to the creation of personalized videos that depict user-specified relations between two subjects, a crucial task for comprehending real-world…
FreeScale: Unleashing the Resolution of Diffusion Models via Tuning-Free Scale Fusion
Haonan Qiu, Shiwei Zhang, Yujie Wei +5
Visual diffusion models achieve remarkable progress, yet they are typically trained at limited resolutions due to the lack of high-resolution data and constrained computation resou…
Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model
Feng Liu, Shiwei Zhang, Xiaofeng Wang +6
As a fundamental backbone for video generation, diffusion models are challenged by low inference speed due to the sequential nature of denoising. Previous methods speed up the mode…
PersonalVideo: High ID-Fidelity Video Customization without Dynamic and Semantic Degradation
Hengjia Li, Haonan Qiu, Shiwei Zhang +6
The current text-to-video (T2V) generation has made significant progress in synthesizing realistic general videos, but it is still under-explored in identity-specific human video g…
DreamVideo-2: Zero-Shot Subject-Driven Video Customization with Precise Motion Control
Yujie Wei, Shiwei Zhang, Hangjie Yuan +9
Recent advances in customized video generation have enabled users to create videos tailored to both specific subjects and motion trajectories. However, existing methods often requi…
EvolveDirector: Approaching Advanced Text-to-Image Generation with Large Vision-Language Models
Rui Zhao, Hangjie Yuan, Yujie Wei +8
Recent advancements in generation models have showcased remarkable capabilities in generating fantastic content. However, most of them are trained on proprietary high-quality data,…
CLIP model is an Efficient Online Lifelong Learner
Leyuan Wang, Liuyu Xiang, Yujie Wei +2
Online Lifelong Learning (OLL) addresses the challenge of learning from continuous and non-stationary data streams. Existing online lifelong learning methods based on image classif…
InstructVideo: Instructing Video Diffusion Models with Human Feedback
Hangjie Yuan, Shiwei Zhang, Xiang Wang +7
Diffusion models have emerged as the de facto paradigm for video generation. However, their reliance on web-scale data of varied quality often yields results that are visually unap…
Hierarchical Spatio-temporal Decoupling for Text-to-Video Generation
Zhiwu Qing, Shiwei Zhang, Jiayu Wang +5
Despite diffusion models having shown powerful abilities to generate photorealistic images, generating videos that are realistic and diverse still remains in its infancy. One of th…
DreamVideo: Composing Your Dream Videos with Customized Subject and Motion
Yujie Wei, Shiwei Zhang, Zhiwu Qing +6
Customized generation using diffusion models has made impressive progress in image generation, but remains unsatisfactory in the challenging video generation task, as it requires t…