1 citations · 3 across the 12 of their papers we have counts for
15 papers
Strike a Chord! Modal Kinetic Typography
Maham Tanveer, Jiyeon Han, Nanxuan Zhao +1
We introduce modal kinetic typography, which animates a vector glyph to express a semantic concept while keeping it legible. Our key idea is to build motion from the glyph's natura…
CraftTrace: Unflattening Videos into Malleable, Creation-Inspired Structures for Generative Editing
Boyu Li, Yuqian Zhou, Duotun Wang +6
Recent generative video editing models enable video content modification (e.g., changing a character) but target short clips. Extending them to full multi-shot videos requires tedi…
Tri-Prompting: Video Diffusion with Unified Control over Scene, Subject, and Motion
Zhenghong Zhou, Xiaohang Zhan, Zhiqin Chen +8
Recent video diffusion models achieve strong visual quality and temporal coherence, but still lack coordinated control over scene layout, customized subject identity, and camera/su…
MultiCOIN: Multi-Modal COntrollable Video INbetweening
Maham Tanveer, Yang Zhou, Simon Niklaus +4
Video inbetweening creates smooth and natural transitions between two image frames, making it an indispensable tool for video editing and long-form video synthesis. Existing works…
EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning
Xuan Ju, Tianyu Wang, Yuqian Zhou +11
Recent advances in foundation models highlight a clear trend toward unification and scaling, showing emergent capabilities across diverse domains. While image generation and editin…
Beyond Simple Edits: X-Planner for Complex Instruction-Based Image Editing
Chun-Hsiao Yeh, Yilin Wang, Nanxuan Zhao +4
Recent diffusion-based image editing methods have significantly advanced text-guided tasks but often struggle to interpret complex, indirect instructions. Moreover, current models…
Comprehensive Relighting: Generalizable and Consistent Monocular Human Relighting and Harmonization
Junying Wang, Jingyuan Liu, Xin Sun +9
This paper introduces Comprehensive Relighting, the first all-in-one approach that can both control and harmonize the lighting from an image or video of humans with arbitrary body…
MotionBridge: Dynamic Video Inbetweening with Flexible Controls
Maham Tanveer, Yang Zhou, Simon Niklaus +4
By generating plausible and smooth transitions between two image frames, video inbetweening is an essential tool for video editing and long video synthesis. Traditional works lack…
SUGAR: Subject-Driven Video Customization in a Zero-Shot Manner
Yufan Zhou, Ruiyi Zhang, Jiuxiang Gu +3
We present SUGAR, a zero-shot method for subject-driven video customization. Given an input image, SUGAR is capable of generating videos for the subject contained in the image and…
UniReal: Universal Image Generation and Editing via Learning Real-world Dynamics
Xi Chen, Zhifei Zhang, He Zhang +10
We introduce UniReal, a unified framework designed to address various image generation and editing tasks. Existing solutions often vary by tasks, yet share fundamental principles:…
LayerFusion: Harmonized Multi-Layer Text-to-Image Generation with Generative Priors
Yusuf Dalva, Yijun Li, Qing Liu +4
Large-scale diffusion models have achieved remarkable success in generating high-quality images from textual descriptions, gaining popularity across various applications. However,…
GroupDiff: Diffusion-based Group Portrait Editing
Yuming Jiang, Nanxuan Zhao, Qing Liu +4
Group portrait editing is highly desirable since users constantly want to add a person, delete a person, or manipulate existing persons. It is also challenging due to the intricate…
Toffee: Efficient Million-Scale Dataset Construction for Subject-Driven Text-to-Image Generation
Yufan Zhou, Ruiyi Zhang, Kaizhi Zheng +5
In subject-driven text-to-image generation, recent works have achieved superior performance by training the model on synthetic datasets containing numerous image pairs. Trained on…
SwapAnything: Enabling Arbitrary Object Swapping in Personalized Visual Editing
Jing Gu, Nanxuan Zhao, Wei Xiong +7
Effective editing of personal content holds a pivotal role in enabling individuals to express their creativity, weaving captivating narratives within their visual stories, and elev…
AnaMoDiff: 2D Analogical Motion Diffusion via Disentangled Denoising
Maham Tanveer, Yizhi Wang, Ruiqi Wang +3
We present AnaMoDiff, a novel diffusion-based method for 2D motion analogies that is applied to raw, unannotated videos of articulated characters. Our goal is to accurately transfe…