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Generating a consistent whole-house VR tour from a floorplan and style reference requires both photorealistic panoramas and cross-view spatial coherence. Pure 2D generators produce appealing single panoramas but re-imagine geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Jinrang Jia , Zhenjia Li , Yijiang Hu , Yifeng Shi

Recent advancements in generative models have provided promising solutions for synthesizing realistic driving videos, which are crucial for training autonomous driving perception models. However, existing approaches often struggle with…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Wei Wu , Xi Guo , Weixuan Tang , Tingxuan Huang , Chiyu Wang , Dongyue Chen , Chenjing Ding

We present a method for text-driven perpetual view generation -- synthesizing long-term videos of various scenes solely, given an input text prompt describing the scene and camera poses. We introduce a novel framework that generates such…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Rafail Fridman , Amit Abecasis , Yoni Kasten , Tali Dekel

The synthesis of spatiotemporally coherent 4D content presents fundamental challenges in computer vision, requiring simultaneous modeling of high-fidelity spatial representations and physically plausible temporal dynamics. Current…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Xiaoyan Liu , Kangrui Li , Yuehao Song , Jiaxin Liu

State-of-the-art video generative models typically learn the distribution of video latents in the VAE space and map them to pixels using a VAE decoder. While this approach can generate high-quality videos, it suffers from slow convergence…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jianhong Bai , Xiaoshi Wu , Xintao Wang , Xiao Fu , Yuanxing Zhang , Qinghe Wang , Xiaoyu Shi , Menghan Xia , Zuozhu Liu , Haoji Hu , Pengfei Wan , Kun Gai

State-of-the-art video generation models produce remarkable photorealism, but they lack the precise control required to align generated content with specific scene requirements. Furthermore, without an underlying explicit geometry, these…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Dana Cohen-Bar , Ido Sobol , Raphael Bensadoun , Shelly Sheynin , Oran Gafni , Or Patashnik , Daniel Cohen-Or , Amit Zohar

Generating long videos that can show complex stories, like movie scenes from scripts, has great promise and offers much more than short clips. However, current methods that use autoregression with diffusion models often struggle because…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Guangcong Zheng , Jianlong Yuan , Bo Wang , Haoyang Huang , Guoqing Ma , Nan Duan

Recent advancements in diffusion models have revolutionized video generation, enabling the creation of high-quality, temporally consistent videos. However, generating high frame-rate (FPS) videos remains a significant challenge due to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Geunmin Hwang , Hyun-kyu Ko , Younghyun Kim , Seungryong Lee , Eunbyung Park

Panoramic videos contain richer spatial information and have attracted tremendous amounts of attention due to their exceptional experience in some fields such as autonomous driving and virtual reality. However, existing datasets for video…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Shilin Yan , Xiaohao Xu , Renrui Zhang , Lingyi Hong , Wenchao Chen , Wenqiang Zhang , Wei Zhang

Motivated by discrete diffusion's success in language-vision modeling, we explore its potential for multi-view generation, a task dominated by continuous approaches. We introduce ViewMask-1-to-3, formulating multi-view synthesis as a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Ruishu Zhu , Zhihao Huang , Jiacheng Sun , Ping Luo , Hongyuan Zhang , Xuelong Li

Generating free-viewpoint videos is critical for immersive VR/AR experience but recent neural advances still lack the editing ability to manipulate the visual perception for large dynamic scenes. To fill this gap, in this paper we propose…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Jiakai Zhang , Xinhang Liu , Xinyi Ye , Fuqiang Zhao , Yanshun Zhang , Minye Wu , Yingliang Zhang , Lan Xu , Jingyi Yu

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder

Video generation models have progressed tremendously through large latent diffusion transformers trained with rectified flow techniques. Yet these models still struggle with geometric inconsistencies, unstable motion, and visual artifacts…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Orest Kupyn , Fabian Manhardt , Federico Tombari , Christian Rupprecht

Video moment retrieval (VMR) aims to locate the most likely video moment(s) corresponding to a text query in untrimmed videos. Training of existing methods is limited by the lack of diverse and generalisable VMR datasets, hindering their…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Dezhao Luo , Shaogang Gong , Jiabo Huang , Hailin Jin , Yang Liu

Panoramic images have advantages in information capacity and scene stability due to their large field of view (FoV). In this paper, we propose a method to synthesize a new dataset of panoramic image. We managed to stitch the images taken…

Computer Vision and Pattern Recognition · Computer Science 2019-09-04 Yuanyou Xu , Kaiwei Wang , Kailun Yang , Dongming Sun , Jia Fu

Video outpainting extends a video beyond its original boundaries by synthesizing missing border content. Compared with image outpainting, it requires not only per-frame spatial plausibility but also long-range temporal coherence, especially…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yueming Pan , Ruoyu Feng , Jianmin Bao , Chong Luo , Nanning Zheng

Controllable spherical panoramic image generation holds substantial applicative potential across a variety of domains.However, it remains a challenging task due to the inherent spherical distortion and geometry characteristics, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Tao Wu , Xuewei Li , Zhongang Qi , Di Hu , Xintao Wang , Ying Shan , Xi Li

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 introduce MVGenMaster, a multi-view diffusion model enhanced with 3D priors to address versatile Novel View Synthesis (NVS) tasks. MVGenMaster leverages 3D priors that are warped using metric depth and camera poses, significantly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Chenjie Cao , Chaohui Yu , Shang Liu , Fan Wang , Xiangyang Xue , Yanwei Fu

$360^\circ$ videos offer a hyper-immersive experience that allows the viewers to explore a dynamic scene from full 360 degrees. To achieve more user-friendly and personalized content creation in $360^\circ$ video format, we seek to lift…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Jing Tan , Shuai Yang , Tong Wu , Jingwen He , Yuwei Guo , Ziwei Liu , Dahua Lin
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