English
Related papers

Related papers: VACE: All-in-One Video Creation and Editing

200 papers

We propose Latte, a novel Latent Diffusion Transformer for video generation. Latte first extracts spatio-temporal tokens from input videos and then adopts a series of Transformer blocks to model video distribution in the latent space. In…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Xin Ma , Yaohui Wang , Xinyuan Chen , Gengyun Jia , Ziwei Liu , Yuan-Fang Li , Cunjian Chen , Yu Qiao

We present an efficient text-to-video generation framework based on latent diffusion models, termed MagicVideo. MagicVideo can generate smooth video clips that are concordant with the given text descriptions. Due to a novel and efficient 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Daquan Zhou , Weimin Wang , Hanshu Yan , Weiwei Lv , Yizhe Zhu , Jiashi Feng

Makeup transfer aims to apply the makeup style from a reference face to a target face and has been increasingly adopted in practical applications. Existing GAN-based approaches typically rely on carefully designed loss functions to balance…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Jian Zhu , Shanyuan Liu , Liuzhuozheng Li , Yue Gong , He Wang , Bo Cheng , Yuhang Ma , Liebucha Wu , Xiaoyu Wu , Dawei Leng , Yuhui Yin , Yang Xu

The Visual Multimethod Assessment Fusion (VMAF) algorithm has recently emerged as a state-of-the-art approach to video quality prediction, that now pervades the streaming and social media industry. However, since VMAF requires the…

Image and Video Processing · Electrical Eng. & Systems 2023-11-21 Abhinau K. Venkataramanan , Cosmin Stejerean , Ioannis Katsavounidis , Alan C. Bovik

A hallmark of human intelligence is the ability to create complex artifacts through structured multi-step processes. Generating procedural tutorials with AI is a longstanding but challenging goal, facing three key obstacles: (1) scarcity of…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Yiren Song , Cheng Liu , Mike Zheng Shou

Generative image editing has recently witnessed extremely fast-paced growth. Some works use high-level conditioning such as text, while others use low-level conditioning. Nevertheless, most of them lack fine-grained control over the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Vidit Goel , Elia Peruzzo , Yifan Jiang , Dejia Xu , Xingqian Xu , Nicu Sebe , Trevor Darrell , Zhangyang Wang , Humphrey Shi

Event cameras excel at high-speed, low-power, and high-dynamic-range scene perception. However, as they fundamentally record only relative intensity changes rather than absolute intensity, the resulting data streams suffer from a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Gang Xu , Zhiyu Zhu , Junhui Hou

Diffusion Transformer has shown remarkable abilities in generating high-fidelity videos, delivering visually coherent frames and rich details over extended durations. However, existing video generation models still fall short in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Zhaoyang Li , Dongjun Qian , Kai Su , Qishuai Diao , Xiangyang Xia , Chang Liu , Wenfei Yang , Tianzhu Zhang , Zehuan Yuan

Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative capabilities. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Li Hu , Xin Gao , Peng Zhang , Ke Sun , Bang Zhang , Liefeng Bo

Generative modeling has recently achieved remarkable success across image, video, and audio domains, demonstrating powerful capabilities for unified representation learning. Yet speech front-end tasks such as speech enhancement (SE), target…

Audio and Speech Processing · Electrical Eng. & Systems 2025-08-12 Ziqian Wang , Zikai Liu , Yike Zhu , Xingchen Li , Boyi Kang , Jixun Yao , Xianjun Xia , Chuanzeng Huang , Lei Xie

This paper proposes a unified diffusion framework (dubbed UniDiffuser) to fit all distributions relevant to a set of multi-modal data in one model. Our key insight is -- learning diffusion models for marginal, conditional, and joint…

Machine Learning · Computer Science 2023-05-31 Fan Bao , Shen Nie , Kaiwen Xue , Chongxuan Li , Shi Pu , Yaole Wang , Gang Yue , Yue Cao , Hang Su , Jun Zhu

Generating temporally-consistent high-fidelity videos can be computationally expensive, especially over longer temporal spans. More-recent Diffusion Transformers (DiTs) -- despite making significant headway in this context -- have only…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Kumara Kahatapitiya , Haozhe Liu , Sen He , Ding Liu , Menglin Jia , Chenyang Zhang , Michael S. Ryoo , Tian Xie

In practical AI workflows, complex tasks often involve chaining multiple generative models, such as using a video or 3D generation model after a 2D image generator. However, distributional mismatches between the output of upstream models…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yujie Zhou , Pengyang Ling , Jiazi Bu , Bingjie Gao , Li Niu

Large-scale text-to-image diffusion models have achieved unprecedented success in image generation and editing. However, extending this success to video editing remains challenging. Recent video editing efforts have adapted pretrained…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Mingshu Cai , Yixuan Li , Osamu Yoshie , Yuya Ieiri

Motivated by the superior performance of image diffusion models, more and more researchers strive to extend these models to the text-based video editing task. Nevertheless, current video editing tasks mainly suffer from the dilemma between…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Yutao Chen , Xingning Dong , Tian Gan , Chunluan Zhou , Ming Yang , Qingpei Guo

Large-scale text-to-video models have shown remarkable abilities, but their direct application in video editing remains challenging due to limited available datasets. Current video editing methods commonly require per-video fine-tuning of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Zhenghao Zhang , Zuozhuo Dai , Long Qin , Weizhi Wang

Achieving machine autonomy and human control often represent divergent objectives in the design of interactive AI systems. Visual generative foundation models such as Stable Diffusion show promise in navigating these goals, especially when…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Can Qin , Shu Zhang , Ning Yu , Yihao Feng , Xinyi Yang , Yingbo Zhou , Huan Wang , Juan Carlos Niebles , Caiming Xiong , Silvio Savarese , Stefano Ermon , Yun Fu , Ran Xu

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

Novel View Synthesis (NVS), which tries to produce a realistic image at the target view given source view images and their corresponding poses, is a fundamental problem in 3D Vision. As this task is heavily under-constrained, some recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Shijie Li , Farhad G. Zanjani , Haitam Ben Yahia , Yuki M. Asano , Juergen Gall , Amirhossein Habibian

While diffusion models show extraordinary talents in text-to-image generation, they may still fail to generate highly aesthetic images. More specifically, there is still a gap between the generated images and the real-world aesthetic images…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Shaojin Wu , Fei Ding , Mengqi Huang , Wei Liu , Qian He