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Generating high-fidelity, temporally consistent videos in autonomous driving scenarios faces a significant challenge, e.g. problematic maneuvers in corner cases. Despite recent video generation works are proposed to tackcle the mentioned…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Junpeng Jiang , Gangyi Hong , Lijun Zhou , Enhui Ma , Hengtong Hu , Xia Zhou , Jie Xiang , Fan Liu , Kaicheng Yu , Haiyang Sun , Kun Zhan , Peng Jia , Miao Zhang

Recent advances in diffusion models have improved controllable streetscape generation and supported downstream perception and planning tasks. However, challenges remain in accurately modeling driving scenes and generating long videos. To…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Jianbiao Mei , Tao Hu , Xuemeng Yang , Licheng Wen , Yu Yang , Tiantian Wei , Yukai Ma , Min Dou , Botian Shi , Yong Liu

The field of generative models has recently witnessed significant progress, with diffusion models showing remarkable performance in image generation. In light of this success, there is a growing interest in exploring the application of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Ariel Lapid , Idan Achituve , Lior Bracha , Ethan Fetaya

Leveraging text, images, structure maps, or motion trajectories as conditional guidance, diffusion models have achieved great success in automated and high-quality video generation. However, generating smooth and rational transition videos…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Zuhao Yang , Jiahui Zhang , Yingchen Yu , Shijian Lu , Song Bai

Text-to-video generation has trailed behind text-to-image generation in terms of quality and diversity, primarily due to the inherent complexities of spatio-temporal modeling and the limited availability of video-text datasets. Recent…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Xiefan Guo , Jinlin Liu , Miaomiao Cui , Liefeng Bo , Di Huang

Large-scale Vision Language Models (LVLMs) exhibit advanced capabilities in tasks that require visual information, including object detection. These capabilities have promising applications in various industrial domains, such as autonomous…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Haruki Sakajo , Hiroshi Takato , Hiroshi Tsutsui , Komei Soda , Hidetaka Kamigaito , Taro Watanabe

Recent text-to-video (T2V) generation methods have seen significant advancements. However, the majority of these works focus on producing short video clips of a single event (i.e., single-scene videos). Meanwhile, recent large language…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Han Lin , Abhay Zala , Jaemin Cho , Mohit Bansal

Modeling disease progression is crucial for improving the quality and efficacy of clinical diagnosis and prognosis, but it is often hindered by a lack of longitudinal medical image monitoring for individual patients. To address this…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Xu Cao , Kaizhao Liang , Kuei-Da Liao , Tianren Gao , Wenqian Ye , Jintai Chen , Zhiguang Ding , Jianguo Cao , James M. Rehg , Jimeng Sun

Autonomous driving is a complex and challenging task that aims at safe motion planning through scene understanding and reasoning. While vision-only autonomous driving methods have recently achieved notable performance, through enhanced…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Chenbin Pan , Burhaneddin Yaman , Tommaso Nesti , Abhirup Mallik , Alessandro G Allievi , Senem Velipasalar , Liu Ren

Text-driven motion generation has achieved substantial progress with the emergence of diffusion models. However, existing methods still struggle to generate complex motion sequences that correspond to fine-grained descriptions, depicting…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Mingyuan Zhang , Huirong Li , Zhongang Cai , Jiawei Ren , Lei Yang , Ziwei Liu

Controllable synthetic data generation can substantially lower the annotation cost of training data. Prior works use diffusion models to generate driving images conditioned on the 3D object layout. However, those models are trained on…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Yunsong Zhou , Michael Simon , Zhenghao Peng , Sicheng Mo , Hongzi Zhu , Minyi Guo , Bolei Zhou

Advances in technology have led to the development of methods that can create desired visual multimedia. In particular, image generation using deep learning has been extensively studied across diverse fields. In comparison, video…

Computer Vision and Pattern Recognition · Computer Science 2021-06-29 Doyeon Kim , Donggyu Joo , Junmo Kim

Retrieval-Augmented Generation (RAG) has demonstrated remarkable success in enhancing Large Language Models (LLMs) through external knowledge integration, yet its application has primarily focused on textual content, leaving the rich domain…

Information Retrieval · Computer Science 2025-02-04 Xubin Ren , Lingrui Xu , Long Xia , Shuaiqiang Wang , Dawei Yin , Chao Huang

Recent advancements in personalized Text-to-Video (T2V) generation have made significant strides in synthesizing character-specific content. However, these methods face a critical limitation: the inability to perform fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Haopeng Fang , Di Qiu , Binjie Mao , He Tang

We introduce a novel diffusion-based video generation method, generating a video showing multiple events given multiple individual sentences from the user. Our method does not require a large-scale video dataset since our method uses a…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Gyeongrok Oh , Jaehwan Jeong , Sieun Kim , Wonmin Byeon , Jinkyu Kim , Sungwoong Kim , Sangpil Kim

The effectiveness of Multimodal Large Language Models (MLLMs) demonstrates a profound capability in multimodal understanding. However, the simultaneous generation of images with coherent texts is still underdeveloped. Addressing this, we…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Kaizhi Zheng , Xuehai He , Xin Eric Wang

We present PhysGen, a novel image-to-video generation method that converts a single image and an input condition (e.g., force and torque applied to an object in the image) to produce a realistic, physically plausible, and temporally…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shaowei Liu , Zhongzheng Ren , Saurabh Gupta , Shenlong Wang

Controllable ultra-long video generation is a fundamental yet challenging task. Although existing methods are effective for short clips, they struggle to scale due to issues such as temporal inconsistency and visual degradation. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Jianxiong Gao , Zhaoxi Chen , Xian Liu , Jianfeng Feng , Chenyang Si , Yanwei Fu , Yu Qiao , Ziwei Liu

Scalable Vector Graphics (SVG) is widely used in front-end development and UI/UX design due to its scalability, editability, and rendering efficiency. However, turning creative ideas into precise vector graphics remains a time-consuming…

Machine Learning · Computer Science 2025-08-14 Feiyu Wang , Zhiyuan Zhao , Yuandong Liu , Da Zhang , Junyu Gao , Hao Sun , Xuelong Li

We present Stable Video 3D (SV3D) -- a latent video diffusion model for high-resolution, image-to-multi-view generation of orbital videos around a 3D object. Recent work on 3D generation propose techniques to adapt 2D generative models for…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Vikram Voleti , Chun-Han Yao , Mark Boss , Adam Letts , David Pankratz , Dmitry Tochilkin , Christian Laforte , Robin Rombach , Varun Jampani
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