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Related papers: OmniDrag: Enabling Motion Control for Omnidirectio…

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Recent progress in text-to-video generation has achieved remarkable realism, yet fine-grained control over camera motion and orientation remains elusive, especially with extreme trajectories (e.g., a 180-degree turnaround, or looking…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Frédéric Fortier-Chouinard , Yannick Hold-Geoffroy , Valentin Deschaintre , Matheus Gadelha , Jean-François Lalonde

To address panoramic distortion, large search space, and identity ambiguity under a 360{\deg} FoV, OmniTrack++ adopts a feedback-driven framework that progressively refines perception with trajectory cues. A DynamicSSM block first…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Kai Luo , Hao Shi , Kunyu Peng , Fei Teng , Sheng Wu , Kaiwei Wang , Kailun Yang

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

Image editing has made great progress on planar images, but panoramic image editing remains underexplored. Due to their spherical geometry and projection distortions, panoramic images present three key challenges: boundary discontinuity,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Zhiao Feng , Xuewei Li , Junjie Yang , Jingchao Li , Yuxin Peng , Xi Li

Recent advancements in personalized Text-to-Video (T2V) generation have made significant strides in synthesizing character-specific content. However, these methods face a critical limitation: the inability to perform fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Haopeng Fang , Di Qiu , Binjie Mao , He Tang

We introduce Motion-I2V, a novel framework for consistent and controllable image-to-video generation (I2V). In contrast to previous methods that directly learn the complicated image-to-video mapping, Motion-I2V factorizes I2V into two…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Xiaoyu Shi , Zhaoyang Huang , Fu-Yun Wang , Weikang Bian , Dasong Li , Yi Zhang , Manyuan Zhang , Ka Chun Cheung , Simon See , Hongwei Qin , Jifeng Dai , Hongsheng Li

We present a unified controllable video generation approach AnimateAnything that facilitates precise and consistent video manipulation across various conditions, including camera trajectories, text prompts, and user motion annotations.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Guojun Lei , Chi Wang , Hong Li , Rong Zhang , Yikai Wang , Weiwei Xu

With the reduced hardware costs of omnidirectional cameras and the proliferation of various extended reality applications, more and more $360^\circ$ videos are being captured. To fully unleash their potential, advanced video analytics is…

Networking and Internet Architecture · Computer Science 2025-08-21 Miao Zhang , Yifei Zhu , Linfeng Shen , Fangxin Wang , Jiangchuan Liu

While recent years have witnessed great progress on using diffusion models for video generation, most of them are simple extensions of image generation frameworks, which fail to explicitly consider one of the key differences between videos…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Jingyun Liang , Yuchen Fan , Kai Zhang , Radu Timofte , Luc Van Gool , Rakesh Ranjan

We present FloVD, a novel video diffusion model for camera-controllable video generation. FloVD leverages optical flow to represent the motions of the camera and moving objects. This approach offers two key benefits. Since optical flow can…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Wonjoon Jin , Qi Dai , Chong Luo , Seung-Hwan Baek , Sunghyun Cho

Image-to-video generation has made remarkable progress with the advancements in diffusion models, yet generating videos with realistic motion remains highly challenging. This difficulty arises from the complexity of accurately modeling…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Chenhui Zhu , Yilu Wu , Shuai Wang , Gangshan Wu , Limin Wang

End-to-end human animation, such as audio-driven talking human generation, has undergone notable advancements in the recent few years. However, existing methods still struggle to scale up as large general video generation models, limiting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Gaojie Lin , Jianwen Jiang , Jiaqi Yang , Zerong Zheng , Chao Liang

An omnidirectional image (ODI) enables viewers to look in every direction from a fixed point through a head-mounted display providing an immersive experience compared to that of a standard image. Designing immersive virtual reality systems…

Computer Vision and Pattern Recognition · Computer Science 2019-08-14 Cagri Ozcinar , Aakanksha Rana , Aljosa Smolic

Video Diffusion Models have been developed for video generation, usually integrating text and image conditioning to enhance control over the generated content. Despite the progress, ensuring consistency across frames remains a challenge,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Tian Xia , Xuweiyi Chen , Sihan Xu

Feed-forward 3D Gaussian splatting (3DGS) models have gained significant popularity due to their ability to generate scenes immediately without needing per-scene optimization. Although omnidirectional images are becoming more popular since…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Suyoung Lee , Jaeyoung Chung , Kihoon Kim , Jaeyoo Huh , Gunhee Lee , Minsoo Lee , Kyoung Mu Lee

Despite recent progress, video diffusion models still struggle to synthesize realistic videos involving highly dynamic motions or requiring fine-grained motion controllability. A central limitation lies in the scarcity of such examples in…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Wonjoon Jin , Jiyun Won , Janghyeok Han , Qi Dai , Chong Luo , Seung-Hwan Baek , Sunghyun Cho

Scalable Vector Graphics (SVGs) are fundamental to digital design and robot control, encoding not only visual structure but also motion paths in interactive drawings. In this work, we introduce RoboSVG, a unified multimodal framework for…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jiuniu Wang , Gongjie Zhang , Quanhao Qian , Junlong Gao , Deli Zhao , Ran Xu

Recent advancements in diffusion models have significantly enhanced the data synthesis with 2D control. Yet, precise 3D control in street view generation, crucial for 3D perception tasks, remains elusive. Specifically, utilizing Bird's-Eye…

Computer Vision and Pattern Recognition · Computer Science 2024-05-06 Ruiyuan Gao , Kai Chen , Enze Xie , Lanqing Hong , Zhenguo Li , Dit-Yan Yeung , Qiang Xu

The spherical domain representation of 360 video/image presents many challenges related to the storage, processing, transmission and rendering of omnidirectional videos (ODV). Models of human visual attention can be used so that only a…

Computer Vision and Pattern Recognition · Computer Science 2020-11-24 Yasser Dahou , Marouane Tliba , Kevin McGuinness , Noel O'Connor

Generating videos guided by camera trajectories poses significant challenges in achieving consistency and generalizability, particularly when both camera and object motions are present. Existing approaches often attempt to learn these…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Guojun Lei , Chi Wang , Yikai Wang , Hong Li , Ying Song , Weiwei Xu
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