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Related papers: 3D-Aware Implicit Motion Control for View-Adaptive…

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Controllable image-to-video (I2V) generation transforms a reference image into a coherent video guided by user-specified control signals. In content creation workflows, precise and simultaneous control over camera motion, object motion, and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Sixiao Zheng , Zimian Peng , Yanpeng Zhou , Yi Zhu , Hang Xu , Xiangru Huang , Yanwei Fu

Recent advances in 3D content generation have amplified demand for dynamic models that are both visually realistic and physically consistent. However, state-of-the-art video diffusion models frequently produce implausible results such as…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Siwei Meng , Yawei Luo , Ping Liu

Data scarcity continues to be a major challenge in the field of robotic manipulation. Although diffusion models provide a promising solution for generating robotic manipulation videos, existing methods largely depend on 2D trajectories,…

Robotics · Computer Science 2025-11-14 Ying Li , Xiaobao Wei , Xiaowei Chi , Yuming Li , Zhongyu Zhao , Hao Wang , Ningning Ma , Ming Lu , Sirui Han , Shanghang Zhang

The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. In order to tackle the problem, we propose a coarse-to-fine method to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-14 Zhongguo Li , Magnus Oskarsson , Anders Heyden

In this paper, we introduce a novel 3D-aware image generation method that leverages 2D diffusion models. We formulate the 3D-aware image generation task as multiview 2D image set generation, and further to a sequential…

Computer Vision and Pattern Recognition · Computer Science 2023-04-03 Jianfeng Xiang , Jiaolong Yang , Binbin Huang , Xin Tong

Beyond traditional hybrid-based video codec, generative video codec could achieve promising compression performance by evolving high-dimensional signals into compact feature representations for bitstream compactness at the encoder side and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Bolin Chen , Ru-Ling Liao , Jie Chen , Yan Ye

In 3D Human Motion Prediction (HMP), conventional methods train HMP models with expensive motion capture data. However, the data collection cost of such motion capture data limits the data diversity, which leads to poor generalizability to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Katsuki Shimbo , Hiromu Taketsugu , Norimichi Ukita

Self driving laboratories (SDLs) are highly automated research environments that leverage advanced technologies to conduct experiments and analyze data with minimal human involvement. These environments often involve delicate laboratory…

Robotics · Computer Science 2026-02-10 Shifa Sulaiman , Tobias Jensen , Francesco Schetter , Simon Bøgh

Recent diffusion-based talking face generation models have demonstrated impressive potential in synthesizing videos that accurately match a speech audio clip with a given reference identity. However, existing approaches still encounter…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xingpei Ma , Jiaran Cai , Yuansheng Guan , Shenneng Huang , Qiang Zhang , Shunsi Zhang

The challenge of dynamic view synthesis from dynamic monocular videos, i.e., synthesizing novel views for free viewpoints given a monocular video of a dynamic scene captured by a moving camera, mainly lies in accurately modeling the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Meng You , Junhui Hou

Previous works concerning single-view hand-held object reconstruction typically rely on supervision from 3D ground-truth models, which are hard to collect in real world. In contrast, readily accessible hand-object videos offer a promising…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Chenyangguang Zhang , Guanlong Jiao , Yan Di , Gu Wang , Ziqin Huang , Ruida Zhang , Fabian Manhardt , Bowen Fu , Federico Tombari , Xiangyang Ji

In the deep learning era, long video generation of high-quality still remains challenging due to the spatio-temporal complexity and continuity of videos. Existing prior works have attempted to model video distribution by representing videos…

Computer Vision and Pattern Recognition · Computer Science 2022-02-23 Sihyun Yu , Jihoon Tack , Sangwoo Mo , Hyunsu Kim , Junho Kim , Jung-Woo Ha , Jinwoo Shin

Speech-driven 3D motion synthesis seeks to create lifelike animations based on human speech, with potential uses in virtual reality, gaming, and the film production. Existing approaches reply solely on speech audio for motion generation,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Wenshuo Peng , Kaipeng Zhang , Sai Qian Zhang

Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, especially in the paradigm of 2D diffusion that lacks 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Chong-Wah Ngo , Tao Mei

Learning an accurate model of the environment is essential for model-based control tasks. Existing methods in robotic visuomotor control usually learn from data with heavily labelled actions, object entities or locations, which can be…

Robotics · Computer Science 2021-07-27 Haoqi Yuan , Ruihai Wu , Andrew Zhao , Haipeng Zhang , Zihan Ding , Hao Dong

Training models to apply linguistic knowledge and visual concepts from 2D images to 3D world understanding is a promising direction that researchers have only recently started to explore. In this work, we design a novel 3D pre-training…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Maria Parelli , Alexandros Delitzas , Nikolas Hars , Georgios Vlassis , Sotirios Anagnostidis , Gregor Bachmann , Thomas Hofmann

The field of advanced text-to-image generation is witnessing the emergence of unified frameworks that integrate powerful text encoders, such as CLIP and T5, with Diffusion Transformer backbones. Although there have been efforts to control…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Liang Chen , Shuai Bai , Wenhao Chai , Weichu Xie , Haozhe Zhao , Leon Vinci , Junyang Lin , Baobao Chang

Appearance of dressed humans undergoes a complex geometric transformation induced not only by the static pose but also by its dynamics, i.e., there exists a number of cloth geometric configurations given a pose depending on the way it has…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Jae Shin Yoon , Duygu Ceylan , Tuanfeng Y. Wang , Jingwan Lu , Jimei Yang , Zhixin Shu , Hyun Soo Park

We consider the task of estimating 3D human pose and shape from videos. While existing frame-based approaches have made significant progress, these methods are independently applied to each image, thereby often leading to inconsistent…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Yun-Chun Chen , Marco Piccirilli , Robinson Piramuthu , Ming-Hsuan Yang

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Bing Li , Cheng Zheng , Wenxuan Zhu , Jinjie Mai , Biao Zhang , Peter Wonka , Bernard Ghanem
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