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Recent advances in diffusion-based video generation have opened new possibilities for controllable video editing, yet realistic video object insertion (VOI) remains challenging due to limited 4D scene understanding and inadequate handling…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Hoiyeong Jin , Hyojin Jang , Jeongho Kim , Junha Hyung , Kinam Kim , Dongjin Kim , Huijin Choi , Hyeonji Kim , Jaegul Choo

We introduce InVi, an approach for inserting or replacing objects within videos (referred to as inpainting) using off-the-shelf, text-to-image latent diffusion models. InVi targets controlled manipulation of objects and blending them…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Nirat Saini , Navaneeth Bodla , Ashish Shrivastava , Avinash Ravichandran , Xiao Zhang , Abhinav Shrivastava , Bharat Singh

In this paper, we introduce a new problem of manipulating a given video by inserting other videos into it. Our main task is, given an object video and a scene video, to insert the object video at a user-specified location in the scene video…

Computer Vision and Pattern Recognition · Computer Science 2019-03-18 Donghoon Lee , Tomas Pfister , Ming-Hsuan Yang

Applying image processing algorithms independently to each video frame often leads to temporal inconsistency in the resulting video. To address this issue, we present a novel and general approach for blind video temporal consistency. Our…

Computer Vision and Pattern Recognition · Computer Science 2020-10-23 Chenyang Lei , Yazhou Xing , Qifeng Chen

In recent years there have been remarkable breakthroughs in image-to-video generation. However, the 3D consistency and camera controllability of generated frames have remained unsolved. Recent studies have attempted to incorporate camera…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Dejia Xu , Yifan Jiang , Chen Huang , Liangchen Song , Thorsten Gernoth , Liangliang Cao , Zhangyang Wang , Hao Tang

Existing person video generation methods either lack the flexibility in controlling both the appearance and motion, or fail to preserve detailed appearance and temporal consistency. In this paper, we tackle the problem of motion transfer…

Computer Vision and Pattern Recognition · Computer Science 2019-08-13 Kun Cheng , Hao-Zhi Huang , Chun Yuan , Lingyiqing Zhou , Wei Liu

Applying an image processing algorithm independently to each video frame often leads to temporal inconsistency in the resulting video. To address this issue, we present a novel and general approach for blind video temporal consistency. Our…

Computer Vision and Pattern Recognition · Computer Science 2022-01-28 Chenyang Lei , Yazhou Xing , Hao Ouyang , Qifeng Chen

We address the task of aligning CAD models to a video sequence of a complex scene containing multiple objects. Our method can process arbitrary videos and fully automatically recover the 9 DoF pose for each object appearing in it, thus…

Computer Vision and Pattern Recognition · Computer Science 2022-01-26 Kevis-Kokitsi Maninis , Stefan Popov , Matthias Nießner , Vittorio Ferrari

This paper addresses key challenges in object-centric representation learning of video. While existing approaches struggle with complex scenes, we propose a novel weakly-supervised framework that emphasises geometric understanding and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Phúc H. Le Khac , Graham Healy , Alan F. Smeaton

Simple as it seems, moving an object to another location within an image is, in fact, a challenging image-editing task that requires re-harmonizing the lighting, adjusting the pose based on perspective, accurately filling occluded regions,…

Graphics · Computer Science 2025-03-12 Xin Yu , Tianyu Wang , Soo Ye Kim , Paul Guerrero , Xi Chen , Qing Liu , Zhe Lin , Xiaojuan Qi

A major challenge in monocular 3D object detection is the limited diversity and quantity of objects in real datasets. While augmenting real scenes with virtual objects holds promise to improve both the diversity and quantity of the objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Yunhao Ge , Hong-Xing Yu , Cheng Zhao , Yuliang Guo , Xinyu Huang , Liu Ren , Laurent Itti , Jiajun Wu

Robots and other smart devices need efficient object-based scene representations from their on-board vision systems to reason about contact, physics and occlusion. Recognized precise object models will play an important role alongside…

Computer Vision and Pattern Recognition · Computer Science 2020-04-10 Kentaro Wada , Edgar Sucar , Stephen James , Daniel Lenton , Andrew J. Davison

Conventional video inpainting is neither object-oriented nor occlusion-aware, making it liable to obvious artifacts when large occluded object regions are inpainted. This paper presents occlusion-aware video object inpainting, which…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Lei Ke , Yu-Wing Tai , Chi-Keung Tang

When perceiving the world from multiple viewpoints, humans have the ability to reason about the complete objects in a compositional manner even when an object is completely occluded from certain viewpoints. Meanwhile, humans are able to…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Chengmin Gao , Bin Li

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

Image-to-video adaptation seeks to efficiently adapt image models for use in the video domain. Instead of finetuning the entire image backbone, many image-to-video adaptation paradigms use lightweight adapters for temporal modeling on top…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Rui Qian , Shuangrui Ding , Dahua Lin

This paper introduces a tuning-free method for both object insertion and subject-driven generation. The task involves composing an object, given multiple views, into a scene specified by either an image or text. Existing methods struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Daniel Winter , Asaf Shul , Matan Cohen , Dana Berman , Yael Pritch , Alex Rav-Acha , Yedid Hoshen

In this work, we present a novel approach for motion customization in video generation, addressing the widespread gap in the exploration of motion representation within video generative models. Recognizing the unique challenges posed by the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Luozhou Wang , Ziyang Mai , Guibao Shen , Yixun Liang , Xin Tao , Pengfei Wan , Di Zhang , Yijun Li , Yingcong Chen

We present a method to estimate depth of a dynamic scene, containing arbitrary moving objects, from an ordinary video captured with a moving camera. We seek a geometrically and temporally consistent solution to this underconstrained…

Computer Vision and Pattern Recognition · Computer Science 2021-08-04 Zhoutong Zhang , Forrester Cole , Richard Tucker , William T. Freeman , Tali Dekel

This paper addresses the problem of tracking moving objects of variable appearance in challenging scenes rich with features and texture. Reliable tracking is of pivotal importance in surveillance applications. It is made particularly…

Computer Vision and Pattern Recognition · Computer Science 2013-09-26 Rhys Martin , Ognjen Arandjelović
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