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Related papers: MultiDreamer3D: Multi-concept 3D Customization wit…

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Generating realistic 3D objects from single-view images requires natural appearance, 3D consistency, and the ability to capture multiple plausible interpretations of unseen regions. Existing approaches often rely on fine-tuning pretrained…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Pufan Li , Bi'an Du , Wei Hu

Text-to-video generation has made remarkable advancements through diffusion models. However, Multi-Concept Video Customization (MCVC) remains a significant challenge. We identify two key challenges for this task: 1) the identity decoupling…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Yuzhou Huang , Ziyang Yuan , Quande Liu , Qiulin Wang , Xintao Wang , Ruimao Zhang , Pengfei Wan , Di Zhang , Kun Gai

In recent times, automatic text-to-3D content creation has made significant progress, driven by the development of pretrained 2D diffusion models. Existing text-to-3D methods typically optimize the 3D representation to ensure that the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Yiwei Ma , Yijun Fan , Jiayi Ji , Haowei Wang , Xiaoshuai Sun , Guannan Jiang , Annan Shu , Rongrong Ji

We introduce PointGauss, a novel point cloud-guided framework for real-time multi-object segmentation in Gaussian Splatting representations. Unlike existing methods that suffer from prolonged initialization and limited multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Wentao Sun , Hanqing Xu , Quanyun Wu , Dedong Zhang , Yiping Chen , Lingfei Ma , John S. Zelek , Jonathan Li

The scale diversity of point cloud data presents significant challenges in developing unified representation learning techniques for 3D vision. Currently, there are few unified 3D models, and no existing pre-training method is equally…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Ziyi Wang , Yanran Zhang , Jie Zhou , Jiwen Lu

Generating realistic and diverse LiDAR point clouds is crucial for autonomous driving simulation. Although previous methods achieve LiDAR point cloud generation from user inputs, they struggle to attain high-quality results while enabling…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Haiyun Wei , Fan Lu , Yunwei Zhu , Zehan Zheng , Weiyi Xue , Lin Shao , Xudong Zhang , Ya Wu , Rong Fu , Guang Chen

This paper aims at high-accuracy 3D object detection in autonomous driving scenario. We propose Multi-View 3D networks (MV3D), a sensory-fusion framework that takes both LIDAR point cloud and RGB images as input and predicts oriented 3D…

Computer Vision and Pattern Recognition · Computer Science 2017-06-23 Xiaozhi Chen , Huimin Ma , Ji Wan , Bo Li , Tian Xia

Denoising diffusion models have demonstrated outstanding results in 2D image generation, yet it remains a challenge to replicate its success in 3D shape generation. In this paper, we propose leveraging multi-view depth, which represents…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zhen Wang , Qiangeng Xu , Feitong Tan , Menglei Chai , Shichen Liu , Rohit Pandey , Sean Fanello , Achuta Kadambi , Yinda Zhang

The customization of text-to-image models has seen significant advancements, yet generating multiple personalized concepts remains a challenging task. Current methods struggle with attribute leakage and layout confusion when handling…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Zebin Yao , Fangxiang Feng , Ruifan Li , Xiaojie Wang

We present a new deep point cloud rendering pipeline through multi-plane projections. The input to the network is the raw point cloud of a scene and the output are image or image sequences from a novel view or along a novel camera…

Computer Vision and Pattern Recognition · Computer Science 2020-06-26 Peng Dai , Yinda Zhang , Zhuwen Li , Shuaicheng Liu , Bing Zeng

Advances in 3D reconstruction have enabled high-quality 3D capture, but require a user to collect hundreds to thousands of images to create a 3D scene. We present CAT3D, a method for creating anything in 3D by simulating this real-world…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Ruiqi Gao , Aleksander Holynski , Philipp Henzler , Arthur Brussee , Ricardo Martin-Brualla , Pratul Srinivasan , Jonathan T. Barron , Ben Poole

Despite advances in neural rendering, due to the scarcity of high-quality 3D datasets and the inherent limitations of multi-view diffusion models, view synthesis and 3D model generation are restricted to low resolutions with suboptimal…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Yihang Luo , Shangchen Zhou , Yushi Lan , Xingang Pan , Chen Change Loy

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulties in acquiring 3D ground truth data for training. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Jiatao Gu , Qingzhe Gao , Shuangfei Zhai , Baoquan Chen , Lingjie Liu , Josh Susskind

While diffusion models have demonstrated remarkable progress in 2D image generation and editing, extending these capabilities to 3D editing remains challenging, particularly in maintaining multi-view consistency. Classical approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yufeng Chi , Huimin Ma , Kafeng Wang , Jianmin Li

Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D generation tends to produce results with inconsistent appearances (e.g., faces on the back view) and inaccurate shapes (e.g., animals with extra…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Cheng Chen , Xiaofeng Yang , Fan Yang , Chengzeng Feng , Zhoujie Fu , Chuan-Sheng Foo , Guosheng Lin , Fayao Liu

Scalable annotation approaches are crucial for constructing extensive 3D-text datasets, facilitating a broader range of applications. However, existing methods sometimes lead to the generation of hallucinated captions, compromising caption…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Tiange Luo , Justin Johnson , Honglak Lee

The three-dimensional reconstruction of scenes from multiple views has made impressive strides in recent years, chiefly by methods correlating isolated feature points, intensities, or curvilinear structure. In the general setting, i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2017-07-14 Anil Usumezbas , Ricardo Fabbri , Benjamin Kimia

We introduce a framework that enables both multi-view character consistency and 3D camera control in video diffusion models through a novel customization data pipeline. We train the character consistency component with recorded volumetric…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Yuancheng Xu , Wenqi Xian , Li Ma , Julien Philip , Ahmet Levent Taşel , Yiwei Zhao , Ryan Burgert , Mingming He , Oliver Hermann , Oliver Pilarski , Rahul Garg , Paul Debevec , Ning Yu

Critical to the registration of point clouds is the establishment of a set of accurate correspondences between points in 3D space. The correspondence problem is generally addressed by the design of discriminative 3D local descriptors on the…

Computer Vision and Pattern Recognition · Computer Science 2023-02-28 Lei Zhou , Siyu Zhu , Zixin Luo , Tianwei Shen , Runze Zhang , Mingmin Zhen , Tian Fang , Long Quan