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Related papers: One Shot Audio to Animated Video Generation

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State-of-the-art Text-to-Video (T2V) diffusion models can generate visually impressive results, yet they still frequently fail to compose complex scenes or follow logical temporal instructions. In this paper, we argue that many errors,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Mariam Hassan , Bastien Van Delft , Wuyang Li , Alexandre Alahi

In recent times, the focus on text-to-audio (TTA) generation has intensified, as researchers strive to synthesize audio from textual descriptions. However, most existing methods, though leveraging latent diffusion models to learn the…

Sound · Computer Science 2024-03-14 Shentong Mo , Jing Shi , Yapeng Tian

Conversation is an essential component of virtual avatar activities in the metaverse. With the development of natural language processing, textual and vocal conversation generation has achieved a significant breakthrough. However,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Yichao Yan , Zanwei Zhou , Zi Wang , Jingnan Gao , Xiaokang Yang

Prevailing Video-to-Audio (V2A) generation models operate offline, assuming an entire video sequence or chunks of frames are available beforehand. This critically limits their use in interactive applications such as live content creation…

Most earlier researches on talking face generation have focused on the synchronization of lip motion and speech content. However, head pose and facial emotions are equally important characteristics of natural faces. While audio-driven…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Changpeng Cai , Guinan Guo , Jiao Li , Junhao Su , Fei Shen , Chenghao He , Jing Xiao , Yuanxu Chen , Lei Dai , Feiyu Zhu

We propose a method for synthesizing photo-realistic digital avatars from only one portrait as the reference. Given a portrait, our method synthesizes a coarse talking head video using driving keypoints features. And with the coarse video,…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Shaoxu Li

The objective of this paper is to jointly synthesize interactive videos and conversational speech from text and reference images. With the ultimate goal of building human-like conversational systems, recent studies have explored talking or…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Ji-Hoon Kim , Junseok Ahn , Doyeop Kwak , Joon Son Chung , Shinji Watanabe

Audio-driven video generation aims to synthesize realistic videos that align with input audio recordings, akin to the human ability to visualize scenes from auditory input. However, existing approaches predominantly focus on exploring…

Graphics · Computer Science 2026-03-17 Kien T. Pham , Yingqing He , Yazhou Xing , Qifeng Chen , Long Chen

The challenge of talking face generation from speech lies in aligning two different modal information, audio and video, such that the mouth region corresponds to input audio. Previous methods either exploit audio-visual representation…

Computer Vision and Pattern Recognition · Computer Science 2022-11-04 Se Jin Park , Minsu Kim , Joanna Hong , Jeongsoo Choi , Yong Man Ro

Human speech is often accompanied by body gestures including arm and hand gestures. We present a method that reenacts a high-quality video with gestures matching a target speech audio. The key idea of our method is to split and re-assemble…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Yang Zhou , Jimei Yang , Dingzeyu Li , Jun Saito , Deepali Aneja , Evangelos Kalogerakis

Storytelling in real-world videos often unfolds through multiple shots -- discontinuous yet semantically connected clips that together convey a coherent narrative. However, existing multi-shot video generation (MSV) methods struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Zhaochong An , Menglin Jia , Haonan Qiu , Zijian Zhou , Xiaoke Huang , Zhiheng Liu , Weiming Ren , Kumara Kahatapitiya , Ding Liu , Sen He , Chenyang Zhang , Tao Xiang , Fanny Yang , Serge Belongie , Tian Xie

Generating conversational gestures from speech audio is challenging due to the inherent one-to-many mapping between audio and body motions. Conventional CNNs/RNNs assume one-to-one mapping, and thus tend to predict the average of all…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Jing Li , Di Kang , Wenjie Pei , Xuefei Zhe , Ying Zhang , Zhenyu He , Linchao Bao

Video generation models are rapidly improving in their ability to synthesize human actions in novel contexts, holding the potential to serve as high-level planners for contextual robot control. To realize this potential, a key research…

Robotics · Computer Science 2025-12-12 James Ni , Zekai Wang , Wei Lin , Amir Bar , Yann LeCun , Trevor Darrell , Jitendra Malik , Roei Herzig

Creating a realistic animatable avatar from a single static portrait remains challenging. Existing approaches often struggle to capture subtle facial expressions, the associated global body movements, and the dynamic background. To address…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Mengchao Wang , Qiang Wang , Fan Jiang , Yaqi Fan , Yunpeng Zhang , Yonggang Qi , Kun Zhao , Mu Xu

We propose the first approach to automatically and jointly synthesize both the synchronous 3D conversational body and hand gestures, as well as 3D face and head animations, of a virtual character from speech input. Our algorithm uses a CNN…

Computer Vision and Pattern Recognition · Computer Science 2021-02-16 Ikhsanul Habibie , Weipeng Xu , Dushyant Mehta , Lingjie Liu , Hans-Peter Seidel , Gerard Pons-Moll , Mohamed Elgharib , Christian Theobalt

The task of audio-driven portrait animation involves generating a talking head video using an identity image and an audio track of speech. While many existing approaches focus on lip synchronization and video quality, few tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Jian Zhang , Weijian Mai , Zhijun Zhang

While image manipulation achieves tremendous breakthroughs (e.g., generating realistic faces) in recent years, video generation is much less explored and harder to control, which limits its applications in the real world. For instance,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-08 Tsun-Hsuan Wang , Yen-Chi Cheng , Chieh Hubert Lin , Hwann-Tzong Chen , Min Sun

Recent advances in video generation have been remarkable, enabling models to produce visually compelling videos with synchronized audio. While existing video generation benchmarks provide comprehensive metrics for visual quality, they lack…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Daili Hua , Xizhi Wang , Bohan Zeng , Xinyi Huang , Hao Liang , Junbo Niu , Xinlong Chen , Quanqing Xu , Wentao Zhang

Human motion video generation has garnered significant research interest due to its broad applications, enabling innovations such as photorealistic singing heads or dynamic avatars that seamlessly dance to music. However, existing surveys…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Haiwei Xue , Xiangyang Luo , Zhanghao Hu , Xin Zhang , Xunzhi Xiang , Yuqin Dai , Jianzhuang Liu , Zhensong Zhang , Minglei Li , Jian Yang , Fei Ma , Zhiyong Wu , Changpeng Yang , Zonghong Dai , Fei Richard Yu

Video-to-audio (V2A) generation is important for video editing and post-processing, enabling the creation of semantics-aligned audio for silent video. However, most existing methods focus on generating short-form audio for short video…

Sound · Computer Science 2024-12-31 Xin Cheng , Xihua Wang , Yihan Wu , Yuyue Wang , Ruihua Song
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