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Bimanual manipulation is crucial in robotics, enabling complex tasks in industrial automation and household services. However, it poses significant challenges due to the high-dimensional action space and intricate coordination requirements.…

Recently video generation has achieved substantial progress with realistic results. Nevertheless, existing AI-generated videos are usually very short clips ("shot-level") depicting a single scene. To deliver a coherent long video…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Xinyuan Chen , Yaohui Wang , Lingjun Zhang , Shaobin Zhuang , Xin Ma , Jiashuo Yu , Yali Wang , Dahua Lin , Yu Qiao , Ziwei Liu

This paper uses the capabilities of latent diffusion models (LDMs) to generate realistic RGB human-object interaction scenes to guide humanoid loco-manipulation planning. To do so, we extract from the generated images both the contact…

Robotics · Computer Science 2025-04-24 Ilyass Taouil , Haizhou Zhao , Angela Dai , Majid Khadiv

This paper introduces EasyAnimate, an efficient and high quality video generation framework that leverages diffusion transformers to achieve high-quality video production, encompassing data processing, model training, and end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Jiaqi Xu , Kunzhe Huang , Xinyi Zou , Yunkuo Chen , Bo Liu , MengLi Cheng , Jun Huang , Xing Shi

Current video generation models excel at creating short, realistic clips, but struggle with longer, multi-scene videos. We introduce \texttt{DreamFactory}, an LLM-based framework that tackles this challenge. \texttt{DreamFactory} leverages…

Artificial Intelligence · Computer Science 2024-08-22 Zhifei Xie , Daniel Tang , Dingwei Tan , Jacques Klein , Tegawend F. Bissyand , Saad Ezzini

Text-to-video diffusion models enable the generation of high-quality videos that follow text instructions, making it easy to create diverse and individual content. However, existing approaches mostly focus on high-quality short video…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Roberto Henschel , Levon Khachatryan , Hayk Poghosyan , Daniil Hayrapetyan , Vahram Tadevosyan , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

Panorama video recently attracts more interest in both study and application, courtesy of its immersive experience. Due to the expensive cost of capturing 360-degree panoramic videos, generating desirable panorama videos by prompts is…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Qian Wang , Weiqi Li , Chong Mou , Xinhua Cheng , Jian Zhang

Video generation models have been used as a robot policy to predict the future states of executing a task conditioned on task description and observation. Previous works ignore their high computational cost and long inference time. To…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Qikang Zhang , Yingjie Lei , Wei Liu , Daochang Liu

Building video world models upon pretrained video generation systems represents an important yet challenging step toward general spatiotemporal intelligence. A world model should possess three essential properties: controllability,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Jianxiong Gao , Zhaoxi Chen , Xian Liu , Junhao Zhuang , Chengming Xu , Jianfeng Feng , Yu Qiao , Yanwei Fu , Chenyang Si , Ziwei Liu

Human motion generation aims to produce plausible human motion sequences according to various conditional inputs, such as text or audio. Despite the feasibility of existing methods in generating motion based on short prompts and simple…

Multimedia · Computer Science 2024-11-12 Bo Han , Hao Peng , Minjing Dong , Yi Ren , Yixuan Shen , Chang Xu

The widespread success of artificial intelligence in fields like natural language processing and computer vision has not yet fully transferred to robotics, where progress is hindered by the lack of large-scale training data and the…

Machine Learning · Computer Science 2025-01-22 William Yue

Video generation models hold substantial potential in areas such as filmmaking. However, current video diffusion models need high computational costs and produce suboptimal results due to extreme complexity of video generation task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Wenhao Li , Yichao Cao , Xiu Su , Xi Lin , Shan You , Mingkai Zheng , Yi Chen , Chang Xu

Diffusion policy has demonstrated promising performance in the field of robotic manipulation. However, its effectiveness has been primarily limited in short-horizon tasks, and its performance significantly degrades in the presence of image…

Robotics · Computer Science 2025-07-08 Kefeng Huang , Tingguang Li , Yuzhen Liu , Zhe Zhang , Jiankun Wang , Lei Han

Recent advances in generative diffusion models have enabled text-controlled synthesis of realistic and diverse images with impressive quality. Despite these remarkable advances, the application of text-to-image generative models in computer…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yulu Gan , Sungwoo Park , Alexander Schubert , Anthony Philippakis , Ahmed M. Alaa

Diffusion models exhibited tremendous progress in image and video generation, exceeding GANs in quality and diversity. However, they are usually trained on very large datasets and are not naturally adapted to manipulate a given input image…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Yaniv Nikankin , Niv Haim , Michal Irani

Generating realistic and controllable human motions, particularly those involving rich multi-character interactions, remains a significant challenge due to data scarcity and the complexities of modeling inter-personal dynamics. To address…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Ruihao Xi , Xuekuan Wang , Yongcheng Li , Shuhua Li , Zichen Wang , Yiwei Wang , Feng Wei , Cairong Zhao

Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains constrained by severe inference costs. Compared with image generation, video synthesis…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Shitong Shao , Lichen Bai , Pengfei Wan , James Kwok , Zeke Xie

Advances in technology have led to the development of methods that can create desired visual multimedia. In particular, image generation using deep learning has been extensively studied across diverse fields. In comparison, video…

Computer Vision and Pattern Recognition · Computer Science 2021-06-29 Doyeon Kim , Donggyu Joo , Junmo Kim

Text-guided generative diffusion models unlock powerful image creation and editing tools. While these have been extended to video generation, current approaches that edit the content of existing footage while retaining structure require…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Patrick Esser , Johnathan Chiu , Parmida Atighehchian , Jonathan Granskog , Anastasis Germanidis

Generalizing to long-horizon manipulation tasks in a zero-shot setting remains a central challenge in robotics. Current multimodal foundation based approaches, despite their capabilities, typically fail to decompose high-level commands into…

Robotics · Computer Science 2025-10-22 Ke Ye , Jiaming Zhou , Yuanfeng Qiu , Jiayi Liu , Shihui Zhou , Kun-Yu Lin , Junwei Liang
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