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Generating semantically and temporally aligned audio content in accordance with video input has become a focal point for researchers, particularly following the remarkable breakthrough in text-to-video generation. In this work, we aim to…

Sound · Computer Science 2025-03-12 Manjie Xu , Chenxing Li , Xinyi Tu , Yong Ren , Rilin Chen , Yu Gu , Wei Liang , Dong Yu

Video generation is a challenging yet pivotal task in various industries, such as gaming, e-commerce, and advertising. One significant unresolved aspect within T2V is the effective visualization of text within generated videos. Despite the…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Lin Liu , Quande Liu , Shengju Qian , Yuan Zhou , Wengang Zhou , Houqiang Li , Lingxi Xie , Qi Tian

Large-scale text-to-video (T2V) diffusion models have great progress in recent years in terms of visual quality, motion and temporal consistency. However, the generation process is still a black box, where all attributes (e.g., appearance,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Jiwen Yu , Xiaodong Cun , Chenyang Qi , Yong Zhang , Xintao Wang , Ying Shan , Jian Zhang

Text-conditioned image-to-video generation (TI2V) aims to synthesize a realistic video starting from a given image (e.g., a woman's photo) and a text description (e.g., "a woman is drinking water."). Existing TI2V frameworks often require…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Haomiao Ni , Bernhard Egger , Suhas Lohit , Anoop Cherian , Ye Wang , Toshiaki Koike-Akino , Sharon X. Huang , Tim K. Marks

We propose a new task named Audio-driven Per-formance Video Generation (APVG), which aims to synthesizethe video of a person playing a certain instrument guided bya given music audio clip. It is a challenging task to gener-ate the…

Computer Vision and Pattern Recognition · Computer Science 2020-11-06 Hao Zhu , Yi Li , Feixia Zhu , Aihua Zheng , Ran He

Text-image-to-video (TI2V) generation is a critical problem for controllable video generation using both semantic and visual conditions. Most existing methods typically add visual conditions to text-to-video (T2V) foundation models by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Bolin Lai , Sangmin Lee , Xu Cao , Xiang Li , James M. Rehg

Recent diffusion methods have made significant progress in generating videos from single images due to their powerful visual generation capabilities. However, challenges persist in image-to-video synthesis, particularly in human video…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Tiantian Wang , Chun-Han Yao , Tao Hu , Mallikarjun Byrasandra Ramalinga Reddy , Ming-Hsuan Yang , Varun Jampani

Video generation remains a challenging task due to spatiotemporal complexity and the requirement of synthesizing diverse motions with temporal consistency. Previous works attempt to generate videos in arbitrary lengths either in an…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Xiaoqian Shen , Xiang Li , Mohamed Elhoseiny

Despite advancements in Text-to-Video (T2V) generation, producing videos with realistic motion remains challenging. Current models often yield static or minimally dynamic outputs, failing to capture complex motions described by text. This…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Penghui Ruan , Pichao Wang , Divya Saxena , Jiannong Cao , Yuhui Shi

Long video generation remains a challenging and compelling topic in computer vision. Diffusion based models, among the various approaches to video generation, have achieved state of the art quality with their iterative denoising procedures.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Siyang Zhang , Harry Yang , Ser-Nam Lim

Most of these text-to-video (T2V) generative models often produce single-scene video clips that depict an entity performing a particular action (e.g., 'a red panda climbing a tree'). However, it is pertinent to generate multi-scene videos…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Hritik Bansal , Yonatan Bitton , Michal Yarom , Idan Szpektor , Aditya Grover , Kai-Wei Chang

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

Audio to Video generation is an interesting problem that has numerous applications across industry verticals including film making, multi-media, marketing, education and others. High-quality video generation with expressive facial movements…

Computer Vision and Pattern Recognition · Computer Science 2020-12-16 Neeraj Kumar , Srishti Goel , Ankur Narang , Mujtaba Hasan

Text-based diffusion models have exhibited remarkable success in generation and editing, showing great promise for enhancing visual content with their generative prior. However, applying these models to video super-resolution remains…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Shangchen Zhou , Peiqing Yang , Jianyi Wang , Yihang Luo , Chen Change Loy

Text-to-image diffusion models (T2I) have demonstrated unprecedented capabilities in creating realistic and aesthetic images. On the contrary, text-to-video diffusion models (T2V) still lag far behind in frame quality and text alignment,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-11 Yabo Zhang , Yuxiang Wei , Xianhui Lin , Zheng Hui , Peiran Ren , Xuansong Xie , Xiangyang Ji , Wangmeng Zuo

Audio is inherently temporal and closely synchronized with the visual world, making it a naturally aligned and expressive control signal for controllable video generation (e.g., movies). Beyond control, directly translating audio into video…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Shuchen Weng , Haojie Zheng , Zheng Chang , Si Li , Boxin Shi , Xinlong Wang

Long-term video generation and prediction remain challenging tasks in computer vision, particularly in partially observable scenarios where cameras are mounted on moving platforms. The interaction between observed image frames and the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Meenakshi Sarkar , Debasish Ghose

Generative diffusion models are developing rapidly and attracting increasing attention due to their wide range of applications. Image-to-Video (I2V) generation has become a major focus in the field of video synthesis. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Ailing Zhang , Lina Lei , Dehong Kong , Zhixin Wang , Jiaqi Xu , Fenglong Song , Chun-Le Guo , Chang Liu , Fan Li , Jie Chen

Foundational world models must be both interactive and preserve spatiotemporal coherence for effective future planning with action choices. However, present models for long video generation have limited inherent world modeling capabilities…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Taiye Chen , Xun Hu , Zihan Ding , Chi Jin

Scalable Vector Graphics (SVG) has become the de facto standard for vector graphics in digital design, offering resolution independence and precise control over individual elements. Despite their advantages, creating high-quality SVG…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Ronghuan Wu , Wanchao Su , Jing Liao
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