activity
20232025
most citedSwapAnything: Enabling Arbitrary Object Swapping in Personalized Visual Editing

1 citations · 2 across the 13 of their papers we have counts for

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10 papers · 1 filter

cs.CV2024

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:…

cs.CV2024

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,…

cs.CV2024

MetaShadow: Object-Centered Shadow Detection, Removal, and Synthesis

Tianyu Wang, Jianming Zhang, Haitian Zheng +7

Shadows are often under-considered or even ignored in image editing applications, limiting the realism of the edited results. In this paper, we introduce MetaShadow, a three-in-one…

cs.CV2024

Refine-by-Align: Reference-Guided Artifacts Refinement through Semantic Alignment

Yizhi Song, Liu He, Zhifei Zhang +8

Personalized image generation has emerged from the recent advancements in generative models. However, these generated personalized images often suffer from localized artifacts such…

cs.CV2024

Generative Image Layer Decomposition with Visual Effects

Jinrui Yang, Qing Liu, Yijun Li +7

Recent advancements in large generative models, particularly diffusion-based methods, have significantly enhanced the capabilities of image editing. However, achieving precise cont…

cs.CV2024

Baking Gaussian Splatting into Diffusion Denoiser for Fast and Scalable Single-stage Image-to-3D Generation and Reconstruction

Yuanhao Cai, He Zhang, Kai Zhang +12

Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt…

cs.CV2024★ 1 cited

Thinking Outside the BBox: Unconstrained Generative Object Compositing

Gemma Canet Tarrés, Zhe Lin, Zhifei Zhang +6

Compositing an object into an image involves multiple non-trivial sub-tasks such as object placement and scaling, color/lighting harmonization, viewpoint/geometry adjustment, and s…

cs.CV2024

Object-level Scene Deocclusion

Zhengzhe Liu, Qing Liu, Chirui Chang +6

Deoccluding the hidden portions of objects in a scene is a formidable task, particularly when addressing real-world scenes. In this paper, we present a new self-supervised PArallel…

cs.CV2024★ 1 cited

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…

cs.CV2024

IMPRINT: Generative Object Compositing by Learning Identity-Preserving Representation

Yizhi Song, Zhifei Zhang, Zhe Lin +7

Generative object compositing emerges as a promising new avenue for compositional image editing. However, the requirement of object identity preservation poses a significant challe…