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Related papers: VIRES: Video Instance Repainting via Sketch and Te…

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Constructing AI models that respond to text instructions is challenging, especially for sequential decision-making tasks. This work introduces a methodology, inspired by unCLIP, for instruction-tuning generative models of behavior without…

Artificial Intelligence · Computer Science 2024-02-06 Shalev Lifshitz , Keiran Paster , Harris Chan , Jimmy Ba , Sheila McIlraith

Video inpainting tasks have seen significant improvements in recent years with the rise of deep neural networks and, in particular, vision transformers. Although these models show promising reconstruction quality and temporal consistency,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Guillaume Thiry , Hao Tang , Radu Timofte , Luc Van Gool

Diffusion models have demonstrated great success in text-to-video (T2V) generation. However, existing methods may face challenges when handling complex (long) video generation scenarios that involve multiple objects or dynamic changes in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Ye Tian , Ling Yang , Haotian Yang , Yuan Gao , Yufan Deng , Jingmin Chen , Xintao Wang , Zhaochen Yu , Xin Tao , Pengfei Wan , Di Zhang , Bin Cui

Recent text-to-video (T2V) diffusion models have made remarkable progress in generating high-quality videos. However, they often struggle to align with complex text prompts, particularly when multiple objects, attributes, or spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Daeun Lee , Jaehong Yoon , Jaemin Cho , Mohit Bansal

We propose a method for generating a temporally remapped video that matches the desired target duration while maximally preserving natural video dynamics. Our approach trains a neural network through self-supervision to recognize and…

Computer Vision and Pattern Recognition · Computer Science 2022-05-12 Simon Jenni , Markus Woodson , Fabian Caba Heilbron

Existing methods for instance segmentation in videos typically involve multi-stage pipelines that follow the tracking-by-detection paradigm and model a video clip as a sequence of images. Multiple networks are used to detect objects in…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Ali Athar , Sabarinath Mahadevan , Aljoša Ošep , Laura Leal-Taixé , Bastian Leibe

Text-driven 3D editing enables user-friendly 3D object or scene editing with text instructions. Due to the lack of multi-view consistency priors, existing methods typically resort to employing 2D generation or editing models to process each…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Liyi Chen , Ruihuang Li , Guowen Zhang , Pengfei Wang , Lei Zhang

During product conceptualization, capturing the non-linear history and cognitive intent is crucial. Traditional sketching tools often lose this context. We introduce DIMES (Design Idea Management and Evolution capture System), a web-based…

Human-Computer Interaction · Computer Science 2026-02-09 Sankar B , Amogh A S , Sandhya Baranwal , Dibakar Sen

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

Visual autoregressive (VAR) models have recently emerged as a promising family of generative models, enabling a wide range of downstream vision tasks such as text-guided image editing. By shifting the editing paradigm from noise…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Tao Xia , Jiawei Liu , Yukun Zhang , Ting Liu , Wei Wang , Lei Zhang

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

Video instance segmentation requires classifying, segmenting, and tracking every object across video frames. Unlike existing approaches that rely on masks, boxes, or category labels, we propose UVIS, a novel Unsupervised Video Instance…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Shuaiyi Huang , Saksham Suri , Kamal Gupta , Sai Saketh Rambhatla , Ser-nam Lim , Abhinav Shrivastava

Conventional video matting outputs one alpha matte for all instances appearing in a video frame so that individual instances are not distinguished. While video instance segmentation provides time-consistent instance masks, results are…

Computer Vision and Pattern Recognition · Computer Science 2023-11-09 Jiachen Li , Roberto Henschel , Vidit Goel , Marianna Ohanyan , Shant Navasardyan , Humphrey Shi

Video instance segmentation is a challenging task that extends image instance segmentation to the video domain. Existing methods either rely only on single-frame information for the detection and segmentation subproblems or handle tracking…

Computer Vision and Pattern Recognition · Computer Science 2022-03-08 Tao Wang , Ning Xu , Kean Chen , Weiyao Lin

Video retrieval is a challenging research topic bridging the vision and language areas and has attracted broad attention in recent years. Previous works have been devoted to representing videos by directly encoding from frame-level…

Computer Vision and Pattern Recognition · Computer Science 2020-06-17 Zerun Feng , Zhimin Zeng , Caili Guo , Zheng Li

Real-world videos often extend over thousands of frames. Existing generative video super-resolution (VSR) approaches, however, face two persistent challenges when processing long sequences: (1) inefficiency due to the heavy cost of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Ziqing Zhang , Kai Liu , Zheng Chen , Xi Li , Yucong Chen , Bingnan Duan , Linghe Kong , Yulun Zhang

As the demand for immersive 3D content grows, the need for intuitive and efficient interaction methods becomes paramount. Current techniques for physically manipulating 3D content within Virtual Reality (VR) often face significant…

Kinematic rigs provide a structured interface for articulating 3D meshes but lack any associated pose space, i.e., an explicit representation of the plausible manifold of joint configurations for a given mesh. Without such a pose space,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Honglin Chen , Karran Pandey , Rundi Wu , Matheus Gadelha , Yannick Hold-Geoffroy , Ayush Tewari , Niloy J. Mitra , Changxi Zheng , Paul Guerrero

Animating hand-drawn sketches using traditional tools is challenging and complex. Sketches provide a visual basis for explanations, and animating these sketches offers an experience of real-time scenarios. We propose an approach for…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Gaurav Rai , Ojaswa Sharma

Despite the rapid advancements in text-to-image (T2I) synthesis, enabling precise visual control remains a significant challenge. Existing works attempted to incorporate multi-facet controls (text and sketch), aiming to enhance the creative…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Zhipeng Chen , Lan Yang , Yonggang Qi , Honggang Zhang , Kaiyue Pang , Ke Li , Yi-Zhe Song
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