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In this paper, we democratise 3D content creation, enabling precise generation of 3D shapes from abstract sketches while overcoming limitations tied to drawing skills. We introduce a novel part-level modelling and alignment framework that…

Computer Vision and Pattern Recognition · Computer Science 2024-06-10 Hmrishav Bandyopadhyay , Subhadeep Koley , Ayan Das , Ayan Kumar Bhunia , Aneeshan Sain , Pinaki Nath Chowdhury , Tao Xiang , Yi-Zhe Song

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

3D world generation is essential for applications such as immersive content creation or autonomous driving simulation. Recent advances in 3D world generation have shown promising results; however, these methods are constrained by grid…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Jaeyoung Chung , Suyoung Lee , Jianfeng Xiang , Jiaolong Yang , Kyoung Mu Lee

Modern 3D generation methods can rapidly create shapes from sparse or single views, but their outputs often lack geometric detail due to computational constraints. We present DetailGen3D, a generative approach specifically designed to…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Ken Deng , Yuan-Chen Guo , Jingxiang Sun , Zi-Xin Zou , Yangguang Li , Xin Cai , Yan-Pei Cao , Yebin Liu , Ding Liang

3D multi object generative models allow us to synthesize a large range of novel 3D multi object scenes and also identify objects, shapes, layouts and their positions. But multi object scenes are difficult to create because of the dataset…

Computer Vision and Pattern Recognition · Computer Science 2019-03-11 Vedant Singh , Manan Oza , Himanshu Vaghela , Pratik Kanani

3D shape generation is a challenging problem due to the high-dimensional output space and complex part configurations of real-world objects. As a result, existing algorithms experience difficulties in accurate generative modeling of 3D…

Computer Vision and Pattern Recognition · Computer Science 2019-06-11 Salman H. Khan , Yulan Guo , Munawar Hayat , Nick Barnes

In this paper, we introduce a hierarchical transformer-based model designed for sophisticated image segmentation tasks, effectively bridging the granularity of part segmentation with the comprehensive scope of object segmentation. At the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Yunfei Xie , Cihang Xie , Alan Yuille , Jieru Mei

Most model-free visual object tracking methods formulate the tracking task as object location estimation given by a 2D segmentation or a bounding box in each video frame. We argue that this representation is limited and instead propose to…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Denys Rozumnyi , Jiri Matas , Marc Pollefeys , Vittorio Ferrari , Martin R. Oswald

This paper presents a new approach for 3D shape generation, enabling direct generative modeling on a continuous implicit representation in wavelet domain. Specifically, we propose a compact wavelet representation with a pair of coarse and…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Ka-Hei Hui , Ruihui Li , Jingyu Hu , Chi-Wing Fu

Recent advances in 3D content creation mostly leverage optimization-based 3D generation via score distillation sampling (SDS). Though promising results have been exhibited, these methods often suffer from slow per-sample optimization,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jiaxiang Tang , Jiawei Ren , Hang Zhou , Ziwei Liu , Gang Zeng

Making generative models 3D-aware bridges the 2D image space and the 3D physical world yet remains challenging. Recent attempts equip a Generative Adversarial Network (GAN) with a Neural Radiance Field (NeRF), which maps 3D coordinates to…

Computer Vision and Pattern Recognition · Computer Science 2022-04-19 Yinghao Xu , Sida Peng , Ceyuan Yang , Yujun Shen , Bolei Zhou

For designing a wide range of everyday objects, the design process should be aware of both the human body and the underlying semantics of the design specification. However, these two objectives present significant challenges to the current…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Michelle Guo , Mia Tang , Hannah Cha , Ruohan Zhang , C. Karen Liu , Jiajun Wu

Generative 3D part assembly involves understanding part relationships and predicting their 6-DoF poses for assembling a realistic 3D shape. Prior work often focus on the geometry of individual parts, neglecting part-whole hierarchies of…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Bi'an Du , Xiang Gao , Wei Hu , Renjie Liao

3D scene generation has quickly become a challenging new research direction, fueled by consistent improvements of 2D generative diffusion models. Most prior work in this area generates scenes by iteratively stitching newly generated frames…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Paul Engstler , Andrea Vedaldi , Iro Laina , Christian Rupprecht

Previous works leveraging video models for image-to-3D scene generation tend to suffer from geometric distortions and blurry content. In this paper, we renovate the pipeline of image-to-3D scene generation by unlocking the potential of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yuhao Wan , Lijuan Liu , Jingzhi Zhou , Zihan Zhou , Xuying Zhang , Dongbo Zhang , Shaohui Jiao , Qibin Hou , Ming-Ming Cheng

Generative video modeling has emerged as a compelling tool to zero-shot reason about plausible physical interactions for open-world manipulation. Yet, it remains a challenge to translate such human-led motions into the low-level actions…

Robotics · Computer Science 2026-01-01 Karthik Dharmarajan , Wenlong Huang , Jiajun Wu , Li Fei-Fei , Ruohan Zhang

Understanding and generating the fine-grained structure of objects -- such as birds with species-specific beaks, wings, and tails -- is a long-standing challenge in computer vision. We propose Chirpy3D, a part-aware multi-view diffusion…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Kam Woh Ng , Jing Yang , Jia Wei Sii , Chee Seng Chan , Jiankang Deng , Yi-Zhe Song , Tao Xiang , Xiatian Zhu

Current image-to-3D approaches suffer from high computational costs and lack scalability for high-resolution outputs. In contrast, we introduce a novel framework to directly generate explicit surface geometry and texture using multi-view 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Haoyu Wu , Meher Gitika Karumuri , Chuhang Zou , Seungbae Bang , Yuelong Li , Dimitris Samaras , Sunil Hadap

The objective of this paper is a model that is able to discover, track and segment multiple moving objects in a video. We make four contributions: First, we introduce an object-centric segmentation model with a depth-ordered layer…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Junyu Xie , Weidi Xie , Andrew Zisserman

Recent approaches have achieved great success in image generation from structured inputs, e.g., semantic segmentation, scene graph or layout. Although these methods allow specification of objects and their locations at image-level, they…

Computer Vision and Pattern Recognition · Computer Science 2020-08-28 Ke Ma , Bo Zhao , Leonid Sigal