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With the increasing popularity of autonomous driving based on the powerful and unified bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view video data with accurate annotation is urgently required.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Xiaofan Li , Yifu Zhang , Xiaoqing Ye

Recent years have seen significant advancements in 3D generation. While methods like score distillation achieve impressive results, they often require extensive per-scene optimization, which limits their time efficiency. On the other hand,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Chen Wang , Jiatao Gu , Xiaoxiao Long , Yuan Liu , Lingjie Liu

Scaling video generation from seconds to minutes faces a critical bottleneck: while short-video data is abundant and high-fidelity, coherent long-form data is scarce and limited to narrow domains. To address this, we propose a training…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Shengqu Cai , Weili Nie , Chao Liu , Julius Berner , Lvmin Zhang , Nanye Ma , Hansheng Chen , Maneesh Agrawala , Leonidas Guibas , Gordon Wetzstein , Arash Vahdat

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

High dynamic range (HDR) novel view synthesis (NVS) aims to reconstruct HDR scenes from multi-exposure low dynamic range (LDR) images. Existing HDR pipelines heavily rely on known camera poses, well-initialized dense point clouds, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Dingqiang Ye , Jiacong Xu , Jianglu Ping , Yuxiang Guo , Chao Fan , Vishal M. Patel

Recent advancements in diffusion models have set new benchmarks in image and video generation, enabling realistic visual synthesis across single- and multi-frame contexts. However, these models still struggle with efficiently and explicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Qihang Zhang , Shuangfei Zhai , Miguel Angel Bautista , Kevin Miao , Alexander Toshev , Joshua Susskind , Jiatao Gu

Diffusion models have emerged as a powerful tool for point cloud generation. A key component that drives the impressive performance for generating high-quality samples from noise is iteratively denoise for thousands of steps. While…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Lemeng Wu , Dilin Wang , Chengyue Gong , Xingchao Liu , Yunyang Xiong , Rakesh Ranjan , Raghuraman Krishnamoorthi , Vikas Chandra , Qiang Liu

In this paper, we present VideoGen, a text-to-video generation approach, which can generate a high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion. We leverage an…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Xin Li , Wenqing Chu , Ye Wu , Weihang Yuan , Fanglong Liu , Qi Zhang , Fu Li , Haocheng Feng , Errui Ding , Jingdong Wang

We address the challenge of generating 3D worlds from textual descriptions. We propose SynCity, a training- and optimization-free approach, which leverages the geometric precision of pre-trained 3D generative models and the artistic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Paul Engstler , Aleksandar Shtedritski , Iro Laina , Christian Rupprecht , Andrea Vedaldi

We present InstantStyleGaussian, an innovative 3D style transfer method based on the 3D Gaussian Splatting (3DGS) scene representation. By inputting a target-style image, it quickly generates new 3D GS scenes. Our method operates on…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Xin-Yi Yu , Jun-Xin Yu , Li-Bo Zhou , Yan Wei , Lin-Lin Ou

In this paper, we introduce a novel 3D-aware image generation method that leverages 2D diffusion models. We formulate the 3D-aware image generation task as multiview 2D image set generation, and further to a sequential…

Computer Vision and Pattern Recognition · Computer Science 2023-04-03 Jianfeng Xiang , Jiaolong Yang , Binbin Huang , Xin Tong

Building an efficient and physically consistent world model from limited observations is a long standing challenge in vision and robotics. Many existing world modeling pipelines are based on implicit generative models, which are hard to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Wenhao Hu , Xuexiang Wen , Xi Li , Gaoang Wang

Recent approaches have demonstrated the promise of using diffusion models to generate interactive and explorable worlds. However, most of these methods face critical challenges such as excessively large parameter sizes, reliance on lengthy…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xiaofeng Mao , Zhen Li , Chuanhao Li , Xiaojie Xu , Kaining Ying , Tong He , Jiangmiao Pang , Yu Qiao , Kaipeng Zhang

The increasing demand for virtual reality applications has highlighted the significance of crafting immersive 3D assets. We present a text-to-3D 360$^{\circ}$ scene generation pipeline that facilitates the creation of comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Shijie Zhou , Zhiwen Fan , Dejia Xu , Haoran Chang , Pradyumna Chari , Tejas Bharadwaj , Suya You , Zhangyang Wang , Achuta Kadambi

View-predictive generative models provide strong priors for lifting object-centric images and videos into 3D and 4D through rendering and score distillation objectives. A question then remains: what about lifting complete multi-object…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Wen-Hsuan Chu , Lei Ke , Katerina Fragkiadaki

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

We present 4DNeX, the first feed-forward framework for generating 4D (i.e., dynamic 3D) scene representations from a single image. In contrast to existing methods that rely on computationally intensive optimization or require multi-frame…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Zhaoxi Chen , Tianqi Liu , Long Zhuo , Jiawei Ren , Zeng Tao , He Zhu , Fangzhou Hong , Liang Pan , Ziwei Liu

In this paper, we report on a parallel freeviewpoint video synthesis algorithm that can efficiently reconstruct a high-quality 3D scene representation of sports scenes. The proposed method focuses on a scene that is captured by multiple…

Computer Vision and Pattern Recognition · Computer Science 2019-08-01 Jun Chen , Ryosuke Watanabe , Keisuke Nonaka , Tomoaki Konno , Hiroshi Sankoh , Sei Naito

Recent advancements in 3D content generation from text or a single image struggle with limited high-quality 3D datasets and inconsistency from 2D multi-view generation. We introduce DiffSplat, a novel 3D generative framework that natively…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Chenguo Lin , Panwang Pan , Bangbang Yang , Zeming Li , Yadong Mu

Constructing photo-realistic Free-Viewpoint Videos (FVVs) of dynamic scenes from multi-view videos remains a challenging endeavor. Despite the remarkable advancements achieved by current neural rendering techniques, these methods generally…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Jiakai Sun , Han Jiao , Guangyuan Li , Zhanjie Zhang , Lei Zhao , Wei Xing