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In computer graphics, animation compression is essential for efficient storage, streaming and reproduction of animated meshes. Previous work has presented efficient techniques for compression by deriving skinning transformations and weights…

Graphics · Computer Science 2023-11-09 Anastasia Moutafidou , Vasileios Toulatzis , Ioannis Fudos

Due to the remarkable progress of deep generative models, animating images has become increasingly efficient, whereas associated results have become increasingly realistic. Current animation-approaches commonly exploit structure…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Yaohui Wang , Di Yang , Francois Bremond , Antitza Dantcheva

We present a technique for zero-shot generation of a 3D model using only a target text prompt. Without any 3D supervision our method deforms the control shape of a limit subdivided surface along with its texture map and normal map to obtain…

Computer Vision and Pattern Recognition · Computer Science 2022-09-07 Nasir Mohammad Khalid , Tianhao Xie , Eugene Belilovsky , Tiberiu Popa

We introduce PhysMotion, a novel framework that leverages principled physics-based simulations to guide intermediate 3D representations generated from a single image and input conditions (e.g., applied force and torque), producing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Xiyang Tan , Ying Jiang , Xuan Li , Zeshun Zong , Tianyi Xie , Yin Yang , Chenfanfu Jiang

Previous motion generation methods are limited to the pre-rigged 3D human model, hindering their applications in the animation of various non-rigged characters. In this work, we present TapMo, a Text-driven Animation Pipeline for…

Graphics · Computer Science 2023-10-20 Jiaxu Zhang , Shaoli Huang , Zhigang Tu , Xin Chen , Xiaohang Zhan , Gang Yu , Ying Shan

Recent AI-based 3D content creation has largely evolved along two paths: feed-forward image-to-3D reconstruction approaches and 3D generative models trained with 2D or 3D supervision. In this work, we show that existing feed-forward…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Suttisak Wizadwongsa , Jinfan Zhou , Edward Li , Jeong Joon Park

Character image animation, which synthesizes videos of reference characters driven by pose sequences, has advanced rapidly but remains largely limited to single-human settings. Existing methods struggle to generalize to multi-humanoid…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Xirui Hu , Yanbo Ding , Jiahao Wang , Tingting Shi , Yali Wang , Guo Zhi Zhi , Weizhan Zhang

Image animation has become a promising area in multimodal research, with a focus on generating videos from reference images. While prior work has largely emphasized generic video generation guided by text, music-driven dance video…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Zhikang Dong , Weituo Hao , Ju-Chiang Wang , Peng Zhang , Pawel Polak

In this work, we develop intuitive controls for editing the style of 3D objects. Our framework, Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which conform to a target text prompt. We consider a disentangled…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Oscar Michel , Roi Bar-On , Richard Liu , Sagie Benaim , Rana Hanocka

We present MAV3D (Make-A-Video3D), a method for generating three-dimensional dynamic scenes from text descriptions. Our approach uses a 4D dynamic Neural Radiance Field (NeRF), which is optimized for scene appearance, density, and motion…

Computer Vision and Pattern Recognition · Computer Science 2023-01-27 Uriel Singer , Shelly Sheynin , Adam Polyak , Oron Ashual , Iurii Makarov , Filippos Kokkinos , Naman Goyal , Andrea Vedaldi , Devi Parikh , Justin Johnson , Yaniv Taigman

Urban scene generation has been developing rapidly recently. However, existing methods primarily focus on generating static and single-frame scenes, overlooking the inherently dynamic nature of real-world driving environments. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Hengwei Bian , Lingdong Kong , Haozhe Xie , Liang Pan , Yu Qiao , Ziwei Liu

Existing methods for reconstructing animatable 3D animals from videos typically rely on sparse semantic keypoints to fit parametric models. However, obtaining such keypoints is labor-intensive, and keypoint detectors trained on limited…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Shanshan Zhong , Jiawei Peng , Zehan Zheng , Zhongzhan Huang , Wufei Ma , Guofeng Zhang , Qihao Liu , Alan Yuille , Jieneng Chen

Objective: While recent advances in text-conditioned generative models have enabled the synthesis of realistic medical images, progress has been largely confined to 2D modalities such as chest X-rays. Extending text-to-image generation to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Daniele Molino , Camillo Maria Caruso , Filippo Ruffini , Paolo Soda , Valerio Guarrasi

Recent advancements in video generation, particularly in diffusion models, have driven notable progress in text-to-video (T2V) and image-to-video (I2V) synthesis. However, challenges remain in effectively integrating dynamic motion signals…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Ziye Li , Hao Luo , Xincheng Shuai , Henghui Ding

Autoregressive models can generate high-quality 3D meshes by sequentially producing vertices and faces, but their token-by-token decoding results in slow inference, limiting practical use in interactive and large-scale applications. We…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Tingrui Shen , Yiheng Zhang , Chen Tang , Chuan Ping , Zixing Zhao , Le Wan , Yuwang Wang , Ronggang Wang , Shengfeng He

Text-guided diffusion models have revolutionized image and video generation and have also been successfully used for optimization-based 3D object synthesis. Here, we instead focus on the underexplored text-to-4D setting and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Huan Ling , Seung Wook Kim , Antonio Torralba , Sanja Fidler , Karsten Kreis

Revolutionary advancements in text-to-image models have unlocked new dimensions for sophisticated content creation, such as text-conditioned image editing, enabling the modification of existing images based on textual guidance. This…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Haoyu Zheng , Wenqiao Zhang , Yaoke Wang , Juncheng Li , Zheqi Lv , Xin Min , Mengze Li , Dongping Zhang , Siliang Tang , Yueting Zhuang

Previous efforts have managed to generate production-ready 3D assets from text or images. However, these methods primarily employ NeRF or 3D Gaussian representations, which are not adept at producing smooth, high-quality geometries required…

Graphics · Computer Science 2024-10-15 Rengan Xie , Wenting Zheng , Kai Huang , Yizheng Chen , Qi Wang , Qi Ye , Wei Chen , Yuchi Huo

Although significant progress has been made in the field of speech-driven 3D facial animation recently, the speech-driven animation of an indispensable facial component, eye gaze, has been overlooked by recent research. This is primarily…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Yixiang Zhuang , Chunshan Ma , Yao Cheng , Xuan Cheng , Jing Liao , Juncong Lin

Due to the fascinating generative performance of text-to-image diffusion models, growing text-to-3D generation works explore distilling the 2D generative priors into 3D, using the score distillation sampling (SDS) loss, to bypass the data…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yu-Jie Yuan , Leif Kobbelt , Jiwen Liu , Yuan Zhang , Pengfei Wan , Yu-Kun Lai , Lin Gao
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