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Related papers: ShapeGen4D: Towards High Quality 4D Shape Generati…

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Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yanqin Jiang , Chaohui Yu , Chenjie Cao , Fan Wang , Weiming Hu , Jin Gao

The goal of conditional image-to-video (cI2V) generation is to create a believable new video by beginning with the condition, i.e., one image and text.The previous cI2V generation methods conventionally perform in RGB pixel space, with…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Cuifeng Shen , Yulu Gan , Chen Chen , Xiongwei Zhu , Lele Cheng , Tingting Gao , Jinzhi Wang

While image manipulation achieves tremendous breakthroughs (e.g., generating realistic faces) in recent years, video generation is much less explored and harder to control, which limits its applications in the real world. For instance,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-08 Tsun-Hsuan Wang , Yen-Chi Cheng , Chieh Hubert Lin , Hwann-Tzong Chen , Min Sun

With the rapid advancement and widespread adoption of VR/AR technologies, there is a growing demand for the creation of high-quality, immersive dynamic scenes. However, existing generation works predominantly concentrate on the creation of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Ke Xing , Hanwen Liang , Dejia Xu , Yuyang Yin , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei

Recent advances in video generation have enabled the synthesis of high-quality and visually realistic clips using diffusion transformer models. However, most existing approaches operate purely in the 2D pixel space and lack explicit…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Yunpeng Bai , Shaoheng Fang , Chaohui Yu , Fan Wang , Qixing Huang

We present 3DScenePrompt, a framework that generates the next video chunk from arbitrary-length input while enabling precise camera control and preserving scene consistency. Unlike methods conditioned on a single image or a short clip, we…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 JoungBin Lee , Jaewoo Jung , Jisang Han , Takuya Narihira , Kazumi Fukuda , Junyoung Seo , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Due to the fascinating generative performance of text-to-image diffusion models, growing text-to-3D generation works explore distilling the 2D generative priors into 3D, using the score distillation sampling (SDS) loss, to bypass the data…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yu-Jie Yuan , Leif Kobbelt , Jiwen Liu , Yuan Zhang , Pengfei Wan , Yu-Kun Lai , Lin Gao

Recent advances in diffusion-based generative models have established a new paradigm for image and video relighting. However, extending these capabilities to 4D relighting remains challenging, due primarily to the scarcity of paired 4D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Zhenghuang Wu , Kang Chen , Zeyu Zhang , Hao Tang

In this paper, we introduce \textbf{DimensionX}, a framework designed to generate photorealistic 3D and 4D scenes from just a single image with video diffusion. Our approach begins with the insight that both the spatial structure of a 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Wenqiang Sun , Shuo Chen , Fangfu Liu , Zilong Chen , Yueqi Duan , Jun Zhang , Yikai Wang

Generating audio from a video's visual context has multiple practical applications in improving how we interact with audio-visual media - for example, enhancing CCTV footage analysis, restoring historical videos (e.g., silent movies), and…

Sound · Computer Science 2024-04-30 Hugo Garrido-Lestache Belinchon , Helina Mulugeta , Adam Haile

World models have made significant progress in modeling dynamic environments; however, most embodied world models are still restricted to 2D representations, lacking the comprehensive multi-view information essential for embodied spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peiyan Tu , Hanxin Zhu , Jingwen Sun , Shaojie Ren , Cong Wang , Jiayi Luo , Xiaoqian Cheng , Zhibo Chen

Significant progress has been made in training large generative models for natural language and images. Yet, the advancement of 3D generative models is hindered by their substantial resource demands for training, along with inefficient,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Ka-Hei Hui , Aditya Sanghi , Arianna Rampini , Kamal Rahimi Malekshan , Zhengzhe Liu , Hooman Shayani , Chi-Wing Fu

A primary bottleneck in large-scale text-to-video generation today is physical consistency and controllability. Despite recent advances, state-of-the-art models often produce unrealistic motions, such as objects falling upward, or abrupt…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Yu Yuan , Xijun Wang , Tharindu Wickremasinghe , Zeeshan Nadir , Bole Ma , Stanley H. Chan

4D head capture aims to generate dynamic topological meshes and corresponding texture maps from videos, which is widely utilized in movies and games for its ability to simulate facial muscle movements and recover dynamic textures in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Xuanchen Li , Yuhao Cheng , Xingyu Ren , Haozhe Jia , Di Xu , Wenhan Zhu , Yichao Yan

3D shape generation aims to produce innovative 3D content adhering to specific conditions and constraints. Existing methods often decompose 3D shapes into a sequence of localized components, treating each element in isolation without…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Ruikai Cui , Weizhe Liu , Weixuan Sun , Senbo Wang , Taizhang Shang , Yang Li , Xibin Song , Han Yan , Zhennan Wu , Shenzhou Chen , Hongdong Li , Pan Ji

We present DriveGen3D, a novel framework for generating high-quality and highly controllable dynamic 3D driving scenes that addresses critical limitations in existing methodologies. Current approaches to driving scene synthesis either…

Immersive applications call for synthesizing spatiotemporal 4D content from casual videos without costly 3D supervision. Existing video-to-4D methods typically rely on manually annotated camera poses, which are labor-intensive and brittle…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Dongyue Lu , Ao Liang , Tianxin Huang , Xiao Fu , Yuyang Zhao , Baorui Ma , Liang Pan , Wei Yin , Lingdong Kong , Wei Tsang Ooi , Ziwei Liu

Recent advances in 3D scene generation produce visually appealing output, but current representations hinder artists' workflows that require modifiable 3D textured mesh scenes for visual effects and game development. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Tobias Sautter , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

In this paper, we consider a novel and practical case for talking face video generation. Specifically, we focus on the scenarios involving multi-people interactions, where the talking context, such as audience or surroundings, is present.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-29 Meidai Xuanyuan , Yuwang Wang , Honglei Guo , Qionghai Dai