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Existing methods for reconstructing interactive scenes primarily focus on replacing reconstructed objects with CAD models retrieved from a limited database, resulting in significant discrepancies between the reconstructed and observed…

Robotics · Computer Science 2023-08-02 Zeyu Zhang , Lexing Zhang , Zaijin Wang , Ziyuan Jiao , Muzhi Han , Yixin Zhu , Song-Chun Zhu , Hangxin Liu

Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This results in a lack of a unified approach to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qihang Zhang , Yinghao Xu , Chaoyang Wang , Hsin-Ying Lee , Gordon Wetzstein , Bolei Zhou , Ceyuan Yang

The process of identifying changes or transformations in a scene along with the ability of reasoning about their causes and effects, is a key aspect of intelligence. In this work we go beyond recent advances in computational perception, and…

Computer Vision and Pattern Recognition · Computer Science 2019-05-30 Tejas Gokhale , Shailaja Sampat , Zhiyuan Fang , Yezhou Yang , Chitta Baral

This paper introduces V$^2$Edit, a novel training-free framework for instruction-guided video and 3D scene editing. Addressing the critical challenge of balancing original content preservation with editing task fulfillment, our approach…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Yanming Zhang , Jun-Kun Chen , Jipeng Lyu , Yu-Xiong Wang

Character video synthesis aims to produce realistic videos of animatable characters within lifelike scenes. As a fundamental problem in the computer vision and graphics community, 3D works typically require multi-view captures for per-case…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Yifang Men , Yuan Yao , Miaomiao Cui , Liefeng Bo

We present a dynamic reconstruction system that receives a casual monocular RGB video as input, and outputs a complete and persistent reconstruction of the scene. In other words, we reconstruct not only the the currently visible parts of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Kirill Mazur , Marwan Taher , Andrew J. Davison

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang

We propose a weakly-supervised approach for conditional image generation of complex scenes where a user has fine control over objects appearing in the scene. We exploit sparse semantic maps to control object shapes and classes, as well as…

Computer Vision and Pattern Recognition · Computer Science 2020-11-23 Dario Pavllo , Aurelien Lucchi , Thomas Hofmann

Generative models have achieved significant progress in advancing 2D image editing, demonstrating exceptional precision and realism. However, they often struggle with consistency and object identity preservation due to their inherent…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yuhuan Xie , Aoxuan Pan , Ming-Xian Lin , Wei Huang , Yi-Hua Huang , Xiaojuan Qi

We propose a method for authoring non-realistic 3D objects (represented as either 3D Gaussian Splats or meshes), that comply with 2D edits from specific viewpoints. Namely, given a 3D object, a user chooses different viewpoints and…

Graphics · Computer Science 2025-04-09 Martin El Mqirmi , Noam Aigerman

Forecasting the evolution of 3D scenes and generating unseen scenarios via occupancy-based world models offers substantial potential for addressing corner cases in autonomous driving systems. While tokenization has revolutionized image and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Zhimin Liao , Ping Wei , Ruijie Zhang , Shuaijia Chen , Haoxuan Wang , Ziyang Ren

This paper presents a novel method for generating diverse 3D human poses in scenes with semantic control. Existing methods heavily rely on the human-scene interaction dataset, resulting in a limited diversity of the generated human poses.…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Bowen Dang , Xi Zhao

Recent Text-to-Video (T2V) models have demonstrated powerful capability in visual simulation of real-world geometry and physical laws, indicating its potential as implicit world models. Inspired by this, we explore the feasibility of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yu Li , Menghan Xia , Gongye Liu , Jianhong Bai , Xintao Wang , Conglang Zhang , Yuxuan Lin , Ruihang Chu , Pengfei Wan , Yujiu Yang

Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains. While these methods have incrementally improved the generated image fidelity and text relevancy, several pivotal…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Oran Gafni , Adam Polyak , Oron Ashual , Shelly Sheynin , Devi Parikh , Yaniv Taigman

Implicit neural representations have shown powerful capacity in modeling real-world 3D scenes, offering superior performance in novel view synthesis. In this paper, we target a more challenging scenario, i.e., joint scene novel view…

Computer Vision and Pattern Recognition · Computer Science 2023-08-08 Yuxin Wang , Wayne Wu , Dan Xu

Using synthesized images to boost the performance of perception models is a long-standing research challenge in computer vision. It becomes more eminent in visual-centric autonomous driving systems with multi-view cameras as some long-tail…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Kairui Yang , Enhui Ma , Jibin Peng , Qing Guo , Di Lin , Kaicheng Yu

There are two prevalent ways to constructing 3D scenes: procedural generation and 2D lifting. Among them, panorama-based 2D lifting has emerged as a promising technique, leveraging powerful 2D generative priors to produce immersive,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Yukun Huang , Jiwen Yu , Yanning Zhou , Jianan Wang , Xintao Wang , Pengfei Wan , Xihui Liu

Numerous diffusion models have recently been applied to image synthesis and editing. However, editing 3D scenes is still in its early stages. It poses various challenges, such as the requirement to design specific methods for different…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Shuangkang Fang , Yufeng Wang , Yi Yang , Yi-Hsuan Tsai , Wenrui Ding , Shuchang Zhou , Ming-Hsuan Yang

We tackle the challenge of generating the infinitely extendable 3D world -- large, continuous environments with coherent geometry and realistic appearance. Existing methods face key challenges: 2D-lifting approaches suffer from geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Sikuang Li , Chen Yang , Jiemin Fang , Taoran Yi , Jia Lu , Jiazhong Cen , Lingxi Xie , Wei Shen , Qi Tian

The creation of 3D scenes has traditionally been both labor-intensive and costly, requiring designers to meticulously configure 3D assets and environments. Recent advancements in generative AI, including text-to-3D and image-to-3D methods,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Ziyang Yan , Yihua Shao , Minwen Liao , Siyu Chen , Nan Wang , Muyuan Lin , Jenq-Neng Hwang , Hao Zhao , Fabio Remondino , Lei Li