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Related papers: SemanticGen: Video Generation in Semantic Space

200 papers

Text-to-video generation poses significant challenges due to the inherent complexity of video data, which spans both temporal and spatial dimensions. It introduces additional redundancy, abrupt variations, and a domain gap between language…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Ziqin Zhou , Yifan Yang , Yuqing Yang , Tianyu He , Houwen Peng , Kai Qiu , Qi Dai , Lili Qiu , Chong Luo , Lingqiao Liu

Scaling video generation from seconds to minutes faces a critical bottleneck: while short-video data is abundant and high-fidelity, coherent long-form data is scarce and limited to narrow domains. To address this, we propose a training…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Shengqu Cai , Weili Nie , Chao Liu , Julius Berner , Lvmin Zhang , Nanye Ma , Hansheng Chen , Maneesh Agrawala , Leonidas Guibas , Gordon Wetzstein , Arash Vahdat

Despite the success of Generative Adversarial Networks (GANs) in image synthesis, there lacks enough understanding on what generative models have learned inside the deep generative representations and how photo-realistic images are able to…

Computer Vision and Pattern Recognition · Computer Science 2020-02-12 Ceyuan Yang , Yujun Shen , Bolei Zhou

Interactive video generation has significant potential for scene simulation and video creation. However, existing methods often struggle with maintaining scene consistency during long video generation under dynamic camera control due to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Xinhang Gao , Junlin Guan , Shuhan Luo , Wenzhuo Li , Guanghuan Tan , Jiacheng Wang

We present Imagen Video, a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high definition videos using a base video generation model and a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-06 Jonathan Ho , William Chan , Chitwan Saharia , Jay Whang , Ruiqi Gao , Alexey Gritsenko , Diederik P. Kingma , Ben Poole , Mohammad Norouzi , David J. Fleet , Tim Salimans

We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable indoor scenes. Unlike prior text-driven methods that often suffer from geometric drift or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Stefan Ainetter , Thomas Deixelberger , Edoardo A. Dominici , Philipp Drescher , Konstantinos Vardis , Markus Steinberger

Contemporary models for generating images show remarkable quality and versatility. Swayed by these advantages, the research community repurposes them to generate videos. Since video content is highly redundant, we argue that naively…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Willi Menapace , Aliaksandr Siarohin , Ivan Skorokhodov , Ekaterina Deyneka , Tsai-Shien Chen , Anil Kag , Yuwei Fang , Aleksei Stoliar , Elisa Ricci , Jian Ren , Sergey Tulyakov

Driving video generation has achieved much progress in controllability, video resolution, and length, but fails to support fine-grained object-level controllability for diverse driving videos, while preserving the spatiotemporal…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Li-Heng Chen , Ke Cheng , Yahui Liu , Lei Shi , Shi-Sheng Huang , Hongbo Fu

We consider the problem of generating plausible and diverse video sequences, when we are only given a start and an end frame. This task is also known as inbetweening, and it belongs to the broader area of stochastic video generation, which…

Computer Vision and Pattern Recognition · Computer Science 2019-06-05 Yunpeng Li , Dominik Roblek , Marco Tagliasacchi

Recent advancements in video generation models, like Stable Video Diffusion, show promising results, but primarily focus on short, single-scene videos. These models struggle with generating long videos that involve multiple scenes, coherent…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Weijia Wu , Mingyu Liu , Zeyu Zhu , Xi Xia , Haoen Feng , Wen Wang , Kevin Qinghong Lin , Chunhua Shen , Mike Zheng Shou

There has been exciting progress in generating images from natural language or layout conditions. However, these methods struggle to faithfully reproduce complex scenes due to the insufficient modeling of multiple objects and their…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Yunnan Wang , Ziqiang Li , Zequn Zhang , Wenyao Zhang , Baao Xie , Xihui Liu , Wenjun Zeng , Xin Jin

The recent renaissance in generative models, driven primarily by the advent of diffusion models and iterative improvement in GAN methods, has enabled many creative applications. However, each advancement is also accompanied by a rise in the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-28 Sanjay Saha , Rashindrie Perera , Sachith Seneviratne , Tamasha Malepathirana , Sanka Rasnayaka , Deshani Geethika , Terence Sim , Saman Halgamuge

We offer a new perspective on approaching the task of video generation. Instead of directly synthesizing a sequence of frames, we propose to render a video by warping one static image with a generative deformation field (GenDeF). Such a…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Wen Wang , Kecheng Zheng , Qiuyu Wang , Hao Chen , Zifan Shi , Ceyuan Yang , Yujun Shen , Chunhua Shen

Recent advances in video generation have made it possible to produce visually compelling videos, with wide-ranging applications in content creation, entertainment, and virtual reality. However, most existing diffusion transformer based…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Teng Hu , Jiangning Zhang , Zihan Su , Ran Yi

We introduce SemanticDraw, a new paradigm of interactive content creation where high-quality images are generated in near real-time from given multiple hand-drawn regions, each encoding prescribed semantic meaning. In order to maximize the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Jaerin Lee , Daniel Sungho Jung , Kanggeon Lee , Kyoung Mu Lee

Sounding Video Generation (SVG) is an audio-video joint generation task challenged by high-dimensional signal spaces, distinct data formats, and different patterns of content information. To address these issues, we introduce a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Mingzhen Sun , Weining Wang , Yanyuan Qiao , Jiahui Sun , Zihan Qin , Longteng Guo , Xinxin Zhu , Jing Liu

Notable breakthroughs in diffusion modeling have propelled rapid improvements in video generation, yet current foundational model still face critical challenges in simultaneously balancing prompt following, motion plausibility, and visual…

The extension of image generation to video generation turns out to be a very difficult task, since the temporal dimension of videos introduces an extra challenge during the generation process. Besides, due to the limitation of memory and…

Computer Vision and Pattern Recognition · Computer Science 2018-12-07 Dinesh Acharya , Zhiwu Huang , Danda Pani Paudel , Luc Van Gool

Video generation requires synthesizing consistent and persistent frames with dynamic content over time. This work investigates modeling the temporal relations for composing video with arbitrary length, from a few frames to even infinite,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-15 Qihang Zhang , Ceyuan Yang , Yujun Shen , Yinghao Xu , Bolei Zhou

Facial expression generation has always been an intriguing task for scientists and researchers all over the globe. In this context, we present our novel approach for generating videos of the six basic facial expressions. Starting from a…

Computer Vision and Pattern Recognition · Computer Science 2023-07-04 Hamza Bouzid , Lahoucine Ballihi
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