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Related papers: Paint3D: Paint Anything 3D with Lighting-Less Text…

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Recent work has demonstrated that volumetric scene representations combined with differentiable volume rendering can enable photo-realistic rendering for challenging scenes that mesh reconstruction fails on. However, these methods entangle…

Computer Vision and Pattern Recognition · Computer Science 2021-03-02 Fanbo Xiang , Zexiang Xu , Miloš Hašan , Yannick Hold-Geoffroy , Kalyan Sunkavalli , Hao Su

Video outpainting aims to adequately complete missing areas at the edges of video frames. Compared to image outpainting, it presents an additional challenge as the model should maintain the temporal consistency of the filled area. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-01-22 Fanda Fan , Chaoxu Guo , Litong Gong , Biao Wang , Tiezheng Ge , Yuning Jiang , Chunjie Luo , Jianfeng Zhan

In this paper, we introduce a novel 3D-aware image generation method that leverages 2D diffusion models. We formulate the 3D-aware image generation task as multiview 2D image set generation, and further to a sequential…

Computer Vision and Pattern Recognition · Computer Science 2023-04-03 Jianfeng Xiang , Jiaolong Yang , Binbin Huang , Xin Tong

Large-scale generative models, such as text-to-image diffusion models, have garnered widespread attention across diverse domains due to their creative and high-fidelity image generation. Nonetheless, existing large-scale diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Younghyun Kim , Geunmin Hwang , Junyu Zhang , Eunbyung Park

We present Paint-it, a text-driven high-fidelity texture map synthesis method for 3D meshes via neural re-parameterized texture optimization. Paint-it synthesizes texture maps from a text description by synthesis-through-optimization,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Kim Youwang , Tae-Hyun Oh , Gerard Pons-Moll

Texturing is a fundamental process in computer graphics. Texture is leveraged to enhance the visualization outcome for a 3D scene. In many cases a texture image cannot cover a large 3D model surface because of its small resolution.…

Computer Vision and Pattern Recognition · Computer Science 2021-03-16 Vasilis Toulatzis , Ioannis Fudos

Recent advances in diffusion models have revolutionized 2D and 3D content creation, yet generating photorealistic dynamic 4D scenes remains a significant challenge. Existing dynamic 4D generation methods typically rely on distilling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Vinayak Gupta , Yunze Man , Yu-Xiong Wang

Diffusion-based methods have achieved prominent success in generating 2D media. However, accomplishing similar proficiencies for scene-level mesh texturing in 3D spatial applications, e.g., XR/VR, remains constrained, primarily due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Bangbang Yang , Wenqi Dong , Lin Ma , Wenbo Hu , Xiao Liu , Zhaopeng Cui , Yuewen Ma

Image inpainting aims to fill in the missing pixels with visually coherent and semantically plausible content. Despite the great progress brought from deep generative models, this task still suffers from i. the difficulties in large-scale…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Siyuan Yang , Lu Zhang , Liqian Ma , Yu Liu , JingJing Fu , You He

3D texture generation is receiving increasing attention, as it enables the creation of realistic and aesthetic texture materials for untextured 3D meshes. However, existing 3D texture generation methods are limited to producing only a few…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Zhiyuan Zhang , Zijian Zhou , Linjun Li , Long Chen , Hao Tang , Yichen Gong

State-of-the-art diffusion models can generate highly realistic images based on various conditioning like text, segmentation, and depth. However, an essential aspect often overlooked is the specific camera geometry used during image…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Andrey Voynov , Amir Hertz , Moab Arar , Shlomi Fruchter , Daniel Cohen-Or

We propose a novel approach for probabilistic generative modeling of 3D shapes. Unlike most existing models that learn to deterministically translate a latent vector to a shape, our model, Point-Voxel Diffusion (PVD), is a unified,…

Computer Vision and Pattern Recognition · Computer Science 2021-08-31 Linqi Zhou , Yilun Du , Jiajun Wu

Current 3D inpainting and object removal methods are largely limited to front-facing scenes, facing substantial challenges when applied to diverse, "unconstrained" scenes where the camera orientation and trajectory are unrestricted. To…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Zhihao Shi , Dong Huo , Yuhongze Zhou , Kejia Yin , Yan Min , Juwei Lu , Xinxin Zuo

Developing a unified pipeline that enables users to remove, re-texture, or replace objects in a versatile manner is crucial for text-guided 3D inpainting. However, there are still challenges in performing multiple 3D inpainting tasks within…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Jingyi Pan , Dan Xu , Qiong Luo

Image inpainting is a fundamental task in computer vision, aiming to restore missing or corrupted regions in images realistically. While recent deep learning approaches have significantly advanced the state-of-the-art, challenges remain in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Jacob Fein-Ashley , Benjamin Fein-Ashley

The field of neural rendering has witnessed significant progress with advancements in generative models and differentiable rendering techniques. Though 2D diffusion has achieved success, a unified 3D diffusion pipeline remains unsettled.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yushi Lan , Fangzhou Hong , Shangchen Zhou , Shuai Yang , Xuyi Meng , Yongwei Chen , Zhaoyang Lyu , Bo Dai , Xingang Pan , Chen Change Loy

As online shopping is growing, the ability for buyers to virtually visualize products in their settings-a phenomenon we define as "Virtual Try-All"-has become crucial. Recent diffusion models inherently contain a world model, rendering them…

Computer Vision and Pattern Recognition · Computer Science 2024-01-26 Mehmet Saygin Seyfioglu , Karim Bouyarmane , Suren Kumar , Amir Tavanaei , Ismail B. Tutar

We introduce Material Coating, a novel image editing task that simulates applying a thin material layer onto an object while preserving its underlying coarse and fine geometry. Material coating is fundamentally different from existing…

Graphics · Computer Science 2025-12-03 Sagie Levy , Elad Aharoni , Matan Levy , Ariel Shamir , Dani Lischinski

Single-image relighting is a challenging task that involves reasoning about the complex interplay between geometry, materials, and lighting. Many prior methods either support only specific categories of images, such as portraits, or require…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Haian Jin , Yuan Li , Fujun Luan , Yuanbo Xiangli , Sai Bi , Kai Zhang , Zexiang Xu , Jin Sun , Noah Snavely

Current state-of-the-art methods for video inpainting typically rely on optical flow or attention-based approaches to inpaint masked regions by propagating visual information across frames. While such approaches have led to significant…