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Recently, the field of text-guided 3D scene generation has garnered significant attention. High-quality generation that aligns with physical realism and high controllability is crucial for practical 3D scene applications. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yang Zhou , Zongjin He , Qixuan Li , Chao Wang

3D object detection from monocular images has proven to be an enormously challenging task, with the performance of leading systems not yet achieving even 10\% of that of LiDAR-based counterparts. One explanation for this performance gap is…

Computer Vision and Pattern Recognition · Computer Science 2018-11-21 Thomas Roddick , Alex Kendall , Roberto Cipolla

Image-based 3D object modeling refers to the process of converting raw optical images to 3D digital representations of the objects. Very often, such models are desired to be dimensionally true, semantically labeled with photorealistic…

Computer Vision and Pattern Recognition · Computer Science 2021-06-29 Rongjun Qin , Xu Huang

3D-consistent image generation from a single 2D semantic label is an important and challenging research topic in computer graphics and computer vision. Although some related works have made great progress in this field, most of the existing…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Bo Li , Yi-ke Li , Zhi-fen He , Bin Liu , Yun-Kun Lai

3D Gaussian Splatting (3DGS) techniques have recently enabled high-quality 3D scene reconstruction and real-time novel view synthesis. These approaches, however, are limited by the pinhole camera model and lack effective modeling of defocus…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yujie Wang , Praneeth Chakravarthula , Baoquan Chen

Recent advancements in large generative models, particularly diffusion-based methods, have significantly enhanced the capabilities of image editing. However, achieving precise control over image composition tasks remains a challenge.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Jinrui Yang , Qing Liu , Yijun Li , Soo Ye Kim , Daniil Pakhomov , Mengwei Ren , Jianming Zhang , Zhe Lin , Cihang Xie , Yuyin Zhou

3D Morphable Model (3DMM) fitting has widely benefited face analysis due to its strong 3D priori. However, previous reconstructed 3D faces suffer from degraded visual verisimilitude due to the loss of fine-grained geometry, which is…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Xiangyu Zhu , Chang Yu , Di Huang , Zhen Lei , Hao Wang , Stan Z. Li

This paper presents a multimodal framework that integrates touch signals (contact points and surface normals) into 3D Gaussian Splatting (3DGS). Our approach enhances scene reconstruction, particularly under challenging conditions like low…

Signal Processing · Electrical Eng. & Systems 2025-08-12 Yuchen Gao , Xiao Xu , Eckehard Steinbach , Daniel E. Lucani , Qi Zhang

We present a novel framework for 3D object-centric representation learning. Our approach effectively decomposes complex scenes into individual objects from a single image in an unsupervised fashion. This method, called slot-guided…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Di Qi , Tong Yang , Xiangyu Zhang

This paper presents a fully automatic framework for extracting editable 3D objects directly from a single photograph. Unlike previous methods which recover either depth maps, point clouds, or mesh surfaces, we aim to recover 3D objects with…

Computer Vision and Pattern Recognition · Computer Science 2020-05-29 Xin Chen , Yuwei Li , Xi Luo , Tianjia Shao , Jingyi Yu , Kun Zhou , Youyi Zheng

Articulated object manipulation remains a critical challenge in robotics due to the complex kinematic constraints and the limited physical reasoning of existing methods. In this work, we introduce ArtGS, a novel framework that extends 3D…

Robotics · Computer Science 2025-07-04 Qiaojun Yu , Xibin Yuan , Yu jiang , Junting Chen , Dongzhe Zheng , Ce Hao , Yang You , Yixing Chen , Yao Mu , Liu Liu , Cewu Lu

We aim to obtain an interpretable, expressive, and disentangled scene representation that contains comprehensive structural and textural information for each object. Previous scene representations learned by neural networks are often…

Computer Vision and Pattern Recognition · Computer Science 2018-12-19 Shunyu Yao , Tzu Ming Harry Hsu , Jun-Yan Zhu , Jiajun Wu , Antonio Torralba , William T. Freeman , Joshua B. Tenenbaum

We introduce Structured 3D Features, a model based on a novel implicit 3D representation that pools pixel-aligned image features onto dense 3D points sampled from a parametric, statistical human mesh surface. The 3D points have associated…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Enric Corona , Mihai Zanfir , Thiemo Alldieck , Eduard Gabriel Bazavan , Andrei Zanfir , Cristian Sminchisescu

Reconstructing a renderable 3D model from images is a useful but challenging task. Recent feedforward 3D reconstruction methods have demonstrated remarkable success in efficiently recovering geometry, but still cannot accurately model the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Zekai Gu , Shuoxuan Feng , Yansong Wang , Hanzhuo Huang , Zhongshuo Du , Chengfeng Zhao , Chengwei Ren , Peng Wang , Yuan Liu

Editing images with instructions to reflect non-rigid motions, camera viewpoint shifts, object deformations, human articulations, and complex interactions, poses a challenging yet underexplored problem in computer vision. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Di Chang , Mingdeng Cao , Yichun Shi , Bo Liu , Shengqu Cai , Shijie Zhou , Weilin Huang , Gordon Wetzstein , Mohammad Soleymani , Peng Wang

Free-moving object reconstruction from monocular video remains challenging, particularly without reliable pose or depth cues and under arbitrary object motion. We introduce OnlineSplatter, a novel online feed-forward framework generating…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Mark He Huang , Lin Geng Foo , Christian Theobalt , Ying Sun , De Wen Soh

Gaussian Splatting has become a popular technique for various 3D Computer Vision tasks, including novel view synthesis, scene reconstruction, and dynamic scene rendering. However, the challenge of natural-looking object insertion, where the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Vsevolod Skorokhodov , Nikita Durasov , Pascal Fua

3D-controllable portrait synthesis has significantly advanced, thanks to breakthroughs in generative adversarial networks (GANs). However, it is still challenging to manipulate existing face images with precise 3D control. While…

Computer Vision and Pattern Recognition · Computer Science 2022-08-25 Yuchen Liu , Zhixin Shu , Yijun Li , Zhe Lin , Richard Zhang , S. Y. Kung

We propose an approach for 3D reconstruction and segmentation of a single object placed on a flat surface from an input video. Our approach is to perform dense depth map estimation for multiple views using a proposed objective function that…

Computer Vision and Pattern Recognition · Computer Science 2016-07-29 Tanmay Gupta , Daeyun Shin , Naren Sivagnanadasan , Derek Hoiem

Controllable image generation has attracted increasing attention in recent years, enabling users to manipulate visual content such as identity and style. However, achieving simultaneous control over the 9D poses (location, size, and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Zhenyuan Qin , Xincheng Shuai , Henghui Ding