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In recent years, Generative Adversarial Networks have achieved impressive results in photorealistic image synthesis. This progress nurtures hopes that one day the classical rendering pipeline can be replaced by efficient models that are…

Computer Vision and Pattern Recognition · Computer Science 2020-03-25 Yiyi Liao , Katja Schwarz , Lars Mescheder , Andreas Geiger

We present a novel method for generating geometrically realistic and consistent orbital videos from a single image of an object. Existing video generation works mostly rely on pixel-wise attention to enforce view consistency across frames.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Rong Wang , Ruyi Zha , Ziang Cheng , Jiayu Yang , Pulak Purkait , Hongdong Li

We present an approach to infer a layer-structured 3D representation of a scene from a single input image. This allows us to infer not only the depth of the visible pixels, but also to capture the texture and depth for content in the scene…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Shubham Tulsiani , Richard Tucker , Noah Snavely

Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Semantic image inpainting is a challenging task where large missing regions have to be filled based on the available visual data. Existing methods which extract information from only a single image generally produce unsatisfactory results…

Computer Vision and Pattern Recognition · Computer Science 2017-07-14 Raymond A. Yeh , Chen Chen , Teck Yian Lim , Alexander G. Schwing , Mark Hasegawa-Johnson , Minh N. Do

One major goal of vision is to infer physical models of objects, surfaces, and their layout from sensors. In this paper, we aim to interpret indoor scenes from one RGBD image. Our representation encodes the layout of orthogonal walls and…

Computer Vision and Pattern Recognition · Computer Science 2018-11-15 Chuhang Zou , Ruiqi Guo , Zhizhong Li , Derek Hoiem

The generation of immersive and navigable 3D environments is increasingly prevalent with the growing adoption of virtual reality and 3D content. However, recent methods face a fundamental limitation: they cannot produce 3D worlds that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Antoine Schnepf , Karim Kassab , Flavian Vasile , Andrew Comport

Single-view indoor scene generation plays a crucial role in a range of real-world applications. However, generating a complete 360{\deg} scene from a single image remains a highly ill-posed and challenging problem. Recent approaches have…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Runmao Yao , Junsheng Zhou , Zhen Dong , Yu-Shen Liu

We address the challenge of creating 3D assets for household articulated objects from a single image. Prior work on articulated object creation either requires multi-view multi-state input, or only allows coarse control over the generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Jiayi Liu , Denys Iliash , Angel X. Chang , Manolis Savva , Ali Mahdavi-Amiri

Automatic generation of a high-quality video from a single image remains a challenging task despite the recent advances in deep generative models. This paper proposes a method that can create a high-resolution, long-term animation using…

Graphics · Computer Science 2019-10-17 Yuki Endo , Yoshihiro Kanamori , Shigeru Kuriyama

Recent advancements in open-world 3D object generation have been remarkable, with image-to-3D methods offering superior fine-grained control over their text-to-3D counterparts. However, most existing models fall short in simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2023-11-15 Minghua Liu , Ruoxi Shi , Linghao Chen , Zhuoyang Zhang , Chao Xu , Xinyue Wei , Hansheng Chen , Chong Zeng , Jiayuan Gu , Hao Su

We propose a dual-domain generative model to estimate a texture map from a single image for colorizing a 3D human model. When estimating a texture map, a single image is insufficient as it reveals only one facet of a 3D object. To provide…

Computer Vision and Pattern Recognition · Computer Science 2022-03-15 Seunggyu Chang , Jungchan Cho , Songhwai Oh

Recently there has been an interest in the potential of learning generative models from a single image, as opposed to from a large dataset. This task is of practical significance, as it means that generative models can be used in domains…

Computer Vision and Pattern Recognition · Computer Science 2020-11-18 Tobias Hinz , Matthew Fisher , Oliver Wang , Stefan Wermter

Autonomous robots typically need to construct representations of their surroundings and adapt their motions to the geometry of their environment. Here, we tackle the problem of constructing a policy model for collision-free motion…

Robotics · Computer Science 2025-05-27 Weiming Zhi , Ziyong Ma , Tianyi Zhang , Matthew Johnson-Roberson

One image to editable dynamic 3D model and video generation is novel direction and change in the research area of single image to 3D representation or 3D reconstruction of image. Gaussian Splatting has demonstrated its advantages in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinwei Lin

We present a system for generating indoor scenes in response to text prompts. The prompts are not limited to a fixed vocabulary of scene descriptions, and the objects in generated scenes are not restricted to a fixed set of object…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Rio Aguina-Kang , Maxim Gumin , Do Heon Han , Stewart Morris , Seung Jean Yoo , Aditya Ganeshan , R. Kenny Jones , Qiuhong Anna Wei , Kailiang Fu , Daniel Ritchie

This paper introduces MIDI, a novel paradigm for compositional 3D scene generation from a single image. Unlike existing methods that rely on reconstruction or retrieval techniques or recent approaches that employ multi-stage…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Zehuan Huang , Yuan-Chen Guo , Xingqiao An , Yunhan Yang , Yangguang Li , Zi-Xin Zou , Ding Liang , Xihui Liu , Yan-Pei Cao , Lu Sheng

Existing view synthesis methods mainly focus on the perspective images and have shown promising results. However, due to the limited field-of-view of the pinhole camera, the performance quickly degrades when large camera movements are…

Computer Vision and Pattern Recognition · Computer Science 2021-04-01 Jiale Xu , Jia Zheng , Yanyu Xu , Rui Tang , Shenghua Gao

The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry, it is nontrivial to texture such a scene perfectly due to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Qi Wang , Ruijie Lu , Xudong Xu , Jingbo Wang , Michael Yu Wang , Bo Dai , Gang Zeng , Dan Xu