13 papers
ZeroGVC: Zero-Shot Generative Video Compression with Autoregressive Diffusion Priors
Yixin Gao, Xiaohan Pan, Lin Liu +3
Recent generative video compression methods leverage powerful generative priors to achieve perceptually pleasing reconstructions. However, most existing approaches require addition…
Occlusion-Aware Physics-Semantic Keyframe Selection for Robust Video Editing
Lin Liu, Zhihan Xiao, Haohang Xu +4
Video editing has recently achieved remarkable progress with diffusion-based generative models, enabling diverse object-level manipulations from natural language instructions. Howe…
Reasoning to Align: Implicit Reasoning in Diffusion Transformers for Video Editing
Yan Li, Lin Liu, Xiaopeng Zhang +1
Instruction-based video editing requires transforming a source video according to a natural-language instruction while preserving irrelevant content and remaining temporally cohere…
DualEraser: Joint Video Object and Effect Removal via Balanced Text-Mask Guidance and Decoupled Locator-Preserver
Yuqing Chen, Lin Liu, Haisu Wu +4
Video object removal frequently struggles to eliminate target objects and their associated complex physical effects (e.g., smoke and light) in real-world scenes. We attribute this…
FineEdit: Fine-Grained Image Edit with Bounding Box Guidance
Haohang Xu, Lin Liu, Zhibo Zhang +3
Diffusion-based image editing models have achieved significant progress in real world applications. However, conventional models typically rely on natural language prompts, which o…
CogniEdit: Dense Gradient Flow Optimization for Fine-Grained Image Editing
Yan Li, Lin Liu, Xiaopeng Zhang +4
Instruction-based image editing with diffusion models has achieved impressive results, yet existing methods struggle with fine-grained instructions specifying precise attributes su…
LoVoRA: Text-guided and Mask-free Video Object Removal and Addition with Learnable Object-aware Localization
Zhihan Xiao, Lin Liu, Yixin Gao +4
Text-guided video editing, particularly for object removal and addition, remains a challenging task due to the need for precise spatial and temporal consistency. Existing methods o…
Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length
Yubo Huang, Hailong Guo, Fangtai Wu +9
Audio-driven avatar interaction demands real-time, streaming, and infinite-length generation -- capabilities fundamentally at odds with the sequential denoising and long-horizon dr…
MEPG:Multi-Expert Planning and Generation for Compositionally-Rich Image Generation
Yuan Zhao, Lin Liu
Text-to-image diffusion models have achieved remarkable image quality, but they still struggle with complex, multiele ment prompts, and limited stylistic diversity. To address thes…
O-DisCo-Edit: Object Distortion Control for Unified Realistic Video Editing
Yuqing Chen, Junjie Wang, Lin Liu +4
Diffusion models have recently advanced video editing, yet controllable editing remains challenging due to the need for precise manipulation of diverse object properties. Current m…
See What You Need: Query-Aware Visual Intelligence through Reasoning-Perception Loops
Zixuan Dong, Baoyun Peng, Yufei Wang +4
Human video comprehension demonstrates dynamic coordination between reasoning and visual attention, adaptively focusing on query-relevant details. However, current long-form video…
Enhancing Long Video Question Answering with Scene-Localized Frame Grouping
Xuyi Yang, Wenhao Zhang, Hongbo Jin +5
Current Multimodal Large Language Models (MLLMs) often perform poorly in long video understanding, primarily due to resource limitations that prevent them from processing all video…
RASA: Replace Anyone, Say Anything -- A Training-Free Framework for Audio-Driven and Universal Portrait Video Editing
Tianrui Pan, Lin Liu, Jie Liu +4
Portrait video editing focuses on modifying specific attributes of portrait videos, guided by audio or video streams. Previous methods typically either concentrate on lip-region re…