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Video Temporal Grounding (VTG), which aims to ground target clips from videos (such as consecutive intervals or disjoint shots) according to custom language queries (e.g., sentences or words), is key for video browsing on social media. Most…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Kevin Qinghong Lin , Pengchuan Zhang , Joya Chen , Shraman Pramanick , Difei Gao , Alex Jinpeng Wang , Rui Yan , Mike Zheng Shou

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

Recently, camera-controlled video generation has seen rapid development, offering more precise control over video generation. However, existing methods predominantly focus on camera control in perspective projection video generation, while…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Chenhao Ji , Chaohui Yu , Junyao Gao , Fan Wang , Cairong Zhao

Recent advancements in Virtual Try-On (VTO) have demonstrated exceptional efficacy in generating realistic images and preserving garment details, largely attributed to the robust generative capabilities of text-to-image (T2I) diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhenchen Wan , Yanwu Xu , Zhaoqing Wang , Feng Liu , Tongliang Liu , Mingming Gong

The rapid growth of e-commerce has intensified the demand for Virtual Try-On (VTO) technologies, enabling customers to realistically visualize products overlaid on their own images. Despite recent advances, existing VTO models face…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Qi Li , Shuwen Qiu , Julien Han , Xingzi Xu , Mehmet Saygin Seyfioglu , Kee Kiat Koo , Karim Bouyarmane

Text-conditioned diffusion models have emerged as powerful tools for high-quality video generation. However, enabling Interactive Video Generation (IVG), where users control motion elements such as object trajectory, remains challenging.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Ishaan Rawal , Suryansh Kumar

While text-to-video diffusion models have advanced significantly, creating coherent long-form content remains unreliable due to stochastic sampling artifacts. This necessitates generating multiple candidates, yet verifying them creates a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Daewon Yoon , Hyeongseok Lee , Wonsik Shin , Sangyu Han , Nojun Kwak

We present Vivid-VR, a DiT-based generative video restoration method built upon an advanced T2V foundation model, where ControlNet is leveraged to control the generation process, ensuring content consistency. However, conventional…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Haoran Bai , Xiaoxu Chen , Canqian Yang , Zongyao He , Sibin Deng , Ying Chen

Modern text-to-video (T2V) diffusion models can synthesize visually compelling clips, yet they remain brittle at fine-scale structure: even state-of-the-art generators often produce distorted faces and hands, warped backgrounds, and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Tejas Panambur , Ishan Rajendrakumar Dave , Chongjian Ge , Ersin Yumer , Xue Bai

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

Text-driven image and video diffusion models have recently achieved unprecedented generation realism. While diffusion models have been successfully applied for image editing, very few works have done so for video editing. We present the…

Computer Vision and Pattern Recognition · Computer Science 2023-02-03 Eyal Molad , Eliahu Horwitz , Dani Valevski , Alex Rav Acha , Yossi Matias , Yael Pritch , Yaniv Leviathan , Yedid Hoshen

Image-to-video generation, which aims to generate a video starting from a given reference image, has drawn great attention. Existing methods try to extend pre-trained text-guided image diffusion models to image-guided video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Songcen Xu , Hang Xu , Xiaodan Liang

Recent advancements in AI-based multimedia generation have enabled the creation of hyper-realistic images and videos, raising concerns about their potential use in spreading misinformation. The widespread accessibility of generative…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Joy Battocchio , Stefano Dell'Anna , Andrea Montibeller , Giulia Boato

As artificial intelligence-generated content (AIGC) continues to evolve, video-to-audio (V2A) generation has emerged as a key area with promising applications in multimedia editing, augmented reality, and automated content creation. While…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Yuhuan You , Xihong Wu , Tianshu Qu

We present \textsc{Vx2Text}, a framework for text generation from multimodal inputs consisting of video plus text, speech, or audio. In order to leverage transformer networks, which have been shown to be effective at modeling language, each…

Computer Vision and Pattern Recognition · Computer Science 2021-02-02 Xudong Lin , Gedas Bertasius , Jue Wang , Shih-Fu Chang , Devi Parikh , Lorenzo Torresani

Video diffusion models have shown great potential in generating high-quality videos, making them an increasingly popular focus. However, their inherent iterative nature leads to substantial computational and time costs. While efforts have…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Xiaofeng Mao , Zhengkai Jiang , Fu-Yun Wang , Jiangning Zhang , Hao Chen , Mingmin Chi , Yabiao Wang , Wenhan Luo

Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regularization or feed-forward deterministic model) to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hanyang Wang , Fangfu Liu , Jiawei Chi , Yueqi Duan

Video composition is the core task of video editing. Although image composition based on diffusion models has been highly successful, it is not straightforward to extend the achievement to video object composition tasks, which not only…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Wei Wang , Yaosen Chen , Yuegen Liu , Qi Yuan , Shubin Yang , Yanru Zhang

Recent Diffusion Transformers (DiTs) have shown impressive capabilities in generating high-quality single-modality content, including images, videos, and audio. However, it is still under-explored whether the transformer-based diffuser can…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Kai Wang , Shijian Deng , Jing Shi , Dimitrios Hatzinakos , Yapeng Tian

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong