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Omnidirectional videos that capture the entire surroundings are employed in a variety of fields such as VR applications and remote sensing. However, their wide field of view often causes unwanted objects to appear in the videos. This…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Ryosuke Seshimo , Mariko Isogawa

Curating datasets for object segmentation is a difficult task. With the advent of large-scale pre-trained generative models, conditional image generation has been given a significant boost in result quality and ease of use. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Mischa Dombrowski , Hadrien Reynaud , Matthew Baugh , Bernhard Kainz

We propose a novel training-free image generation algorithm that precisely controls the occlusion relationships between objects in an image. Existing image generation methods typically rely on prompts to influence occlusion, which often…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Xiaohang Zhan , Dingming Liu

We tackle the challenge of generating dynamic 4D scenes from monocular, multi-object videos with heavy occlusions, and introduce GenMOJO, a novel approach that integrates rendering-based deformable 3D Gaussian optimization with generative…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Wen-Hsuan Chu , Lei Ke , Jianmeng Liu , Mingxiao Huo , Pavel Tokmakov , Katerina Fragkiadaki

The objective of this paper is a model that is able to discover, track and segment multiple moving objects in a video. We make four contributions: First, we introduce an object-centric segmentation model with a depth-ordered layer…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Junyu Xie , Weidi Xie , Andrew Zisserman

Objects moving at high speed appear significantly blurred when captured with cameras. The blurry appearance is especially ambiguous when the object has complex shape or texture. In such cases, classical methods, or even humans, are unable…

Computer Vision and Pattern Recognition · Computer Science 2021-11-23 Denys Rozumnyi , Martin R. Oswald , Vittorio Ferrari , Jiri Matas , Marc Pollefeys

In the evolving landscape of video enhancement and editing methodologies, a majority of deep learning techniques often rely on extensive datasets of observed input and ground truth sequence pairs for optimal performance. Such reliance often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Gaurav Shrivastava , Ser-Nam Lim , Abhinav Shrivastava

Blind video decaptioning is a problem of automatically removing text overlays and inpainting the occluded parts in videos without any input masks. While recent deep learning based inpainting methods deal with a single image and mostly…

Computer Vision and Pattern Recognition · Computer Science 2019-05-09 Dahun Kim , Sanghyun Woo , Joon-Young Lee , In So Kweon

This paper aims to recover the intrinsic reflectance layer and shading layer given a single image. Though this intrinsic image decomposition problem has been studied for decades, it remains a significant challenge in cases of complex…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Xiaodong Wang , Zijun He , Xin Yuan

Gaussian splatting typically requires dense observations of the scene and can fail to reconstruct occluded and unobserved areas. We propose a latent diffusion model to reconstruct a complete 3D scene with Gaussian splats, including the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Ziwei Liao , Mohamed Sayed , Steven L. Waslander , Sara Vicente , Daniyar Turmukhambetov , Michael Firman

We address the problem of 3D inconsistency of image inpainting based on diffusion models. We propose a generative model using image pairs that belong to the same scene. To achieve the 3D-consistent and semantically coherent inpainting, we…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Leonid Antsfeld , Boris Chidlovskii

Image inpainting refers to the restoration of an image with missing regions in a way that is not detectable by the observer. The inpainting regions can be of any size and shape. This is an ill-posed inverse problem that does not have a…

Computer Vision and Pattern Recognition · Computer Science 2022-05-05 Coloma Ballester , Aurelie Bugeau , Samuel Hurault , Simone Parisotto , Patricia Vitoria

Recently, how to achieve precise image editing has attracted increasing attention, especially given the remarkable success of text-to-image generation models. To unify various spatial-aware image editing abilities into one framework, we…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yueru Jia , Yuhui Yuan , Aosong Cheng , Chuke Wang , Ji Li , Huizhu Jia , Shanghang Zhang

Recent studies on motion estimation have advocated an optimized motion representation that is globally consistent across the entire video, preferably for every pixel. This is challenging as a uniform representation may not account for the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Rui Li , Dong 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

Object compositing based on 2D images is a challenging problem since it typically involves multiple processing stages such as color harmonization, geometry correction and shadow generation to generate realistic results. Furthermore,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Yizhi Song , Zhifei Zhang , Zhe Lin , Scott Cohen , Brian Price , Jianming Zhang , Soo Ye Kim , Daniel Aliaga

Our brain can effortlessly recognize objects even when partially hidden from view. Seeing the visible of the hidden is called amodal completion; however, this task remains a challenge for generative AI despite rapid progress. We propose to…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Katherine Xu , Lingzhi Zhang , Jianbo Shi

The objective of this paper is to be able to separate a video into its natural layers, and to control which of the separated layers to attend to. For example, to be able to separate reflections, transparency or object motion. We make the…

Computer Vision and Pattern Recognition · Computer Science 2019-10-25 Jean-Baptiste Alayrac , João Carreira , Relja Arandjelović , Andrew Zisserman

Image composition is a complex task which requires a lot of information about the scene for an accurate and realistic composition, such as perspective, lighting, shadows, occlusions, and object interactions. Previous methods have…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Amr Ghoneim , Jiju Poovvancheri , Yasushi Akiyama , Dong Chen

Recent video inpainting methods have made remarkable progress by utilizing explicit guidance, such as optical flow, to propagate cross-frame pixels. However, there are cases where cross-frame recurrence of the masked video is not available,…

Computer Vision and Pattern Recognition · Computer Science 2023-07-18 Yongsheng Yu , Heng Fan , Libo Zhang
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