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Object permanence in humans is a fundamental cue that helps in understanding persistence of objects, even when they are fully occluded in the scene. Present day methods in object segmentation do not account for this amodal nature of the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Kaihua Chen , Deva Ramanan , Tarasha Khurana

We present an approach to semi-supervised video object segmentation, in the context of the DAVIS 2017 challenge. Our approach combines category-based object detection, category-independent object appearance segmentation and temporal object…

Computer Vision and Pattern Recognition · Computer Science 2017-07-21 Gilad Sharir , Eddie Smolyansky , Itamar Friedman

We propose a light-weight variational framework for online tracking of object segmentations in videos based on optical flow and image boundaries. While high-end computer vision methods on this task rely on sequence specific training of…

Computer Vision and Pattern Recognition · Computer Science 2020-08-17 Amirhossein Kardoost , Sabine Müller , Joachim Weickert , Margret Keuper

Imagine trying to track one particular fruitfly in a swarm of hundreds. Higher biological visual systems have evolved to track moving objects by relying on both appearance and motion features. We investigate if state-of-the-art deep neural…

Computer Vision and Pattern Recognition · Computer Science 2021-06-04 Drew Linsley , Girik Malik , Junkyung Kim , Lakshmi N Govindarajan , Ennio Mingolla , Thomas Serre

We present the first real-time system capable of tracking and reconstructing, individually, every visible object in a given scene, without any form of prior on the rigidness of the objects, texture existence, or object category. In contrast…

Robotics · Computer Science 2022-10-11 Haonan Chang , Abdeslam Boularias

Existing deep learning based unsupervised video object segmentation methods still rely on ground-truth segmentation masks to train. Unsupervised in this context only means that no annotated frames are used during inference. As obtaining…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Sahir Shrestha , Mohammad Ali Armin , Hongdong Li , Nick Barnes

In order to learn object segmentation models in videos, conventional methods require a large amount of pixel-wise ground truth annotations. However, collecting such supervised data is time-consuming and labor-intensive. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2019-01-09 Yi-Wen Chen , Yi-Hsuan Tsai , Chu-Ya Yang , Yen-Yu Lin , Ming-Hsuan Yang

Perception of the visually disjoint surfaces of our cluttered world as whole objects, physically distinct from those overlapping them, is a cognitive phenomenon called objectness that forms the basis of our visual perception. Shared by all…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Douglas Poland , Amar Saini

Segmenting foreground object from a video is a challenging task because of the large deformations of the objects, occlusions, and background clutter. In this paper, we propose a frame-by-frame but computationally efficient approach for…

Computer Vision and Pattern Recognition · Computer Science 2017-06-30 Aditya Vora , Shanmuganathan Raman

The segmentation of transparent objects can be very useful in computer vision applications. However, because they borrow texture from their background and have a similar appearance to their surroundings, transparent objects are not handled…

Computer Vision and Pattern Recognition · Computer Science 2015-11-24 Yichao Xu , Hajime Nagahara , Atsushi Shimada , Rin-ichiro Taniguchi

Occlusion is one of the most significant challenges encountered by object detectors and trackers. While both object detection and tracking has received a lot of attention in the past, most existing methods in this domain do not target…

Computer Vision and Pattern Recognition · Computer Science 2021-06-22 Satyaki Chakraborty , Martial Hebert

The goal of this paper is to discover, segment, and track independently moving objects in complex visual scenes. Previous approaches have explored the use of optical flow for motion segmentation, leading to imperfect predictions due to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Junyu Xie , Weidi Xie , Andrew Zisserman

Learning object segmentation in image and video datasets without human supervision is a challenging problem. Humans easily identify moving salient objects in videos using the gestalt principle of common fate, which suggests that what moves…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Silky Singh , Shripad Deshmukh , Mausoom Sarkar , Balaji Krishnamurthy

Visual object tracking is an important task in computer vision, which has many real-world applications, e.g., video surveillance, visual navigation. Visual object tracking also has many challenges, e.g., object occlusion and deformation. To…

Computer Vision and Pattern Recognition · Computer Science 2022-04-26 Ruize Han , Wei Feng , Qing Guo , Qinghua Hu

Artificial objects usually have very stable shape features, which are stable, persistent properties in geometry. They can provide evidence for object recognition. Shape features are more stable and more distinguishing than appearance…

Computer Vision and Pattern Recognition · Computer Science 2023-06-27 Hui Wei , Fu-yu Tang

Most model-free visual object tracking methods formulate the tracking task as object location estimation given by a 2D segmentation or a bounding box in each video frame. We argue that this representation is limited and instead propose to…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Denys Rozumnyi , Jiri Matas , Marc Pollefeys , Vittorio Ferrari , Martin R. Oswald

Tracking segmentation masks of multiple instances has been intensively studied, but still faces two fundamental challenges: 1) the requirement of large-scale, frame-wise annotation, and 2) the complexity of two-stage approaches. To resolve…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Yang Fu , Sifei Liu , Umar Iqbal , Shalini De Mello , Humphrey Shi , Jan Kautz

Despite the success of many advanced tracking methods in this area, tracking targets with drastic variation of appearance such as deformation, view change and partial occlusion in video sequences is still a challenge in practical…

Computer Vision and Pattern Recognition · Computer Science 2016-11-15 Suofei Zhang , Zhixin Sun , Xu Cheng , Zhenyang Wu

We address the problem of discovering part segmentations of articulated objects without supervision. In contrast to keypoints, part segmentations provide information about part localizations on the level of individual pixels. Capturing both…

Computer Vision and Pattern Recognition · Computer Science 2020-09-11 Sandro Braun , Patrick Esser , Björn Ommer

Object Permanence allows people to reason about the location of non-visible objects, by understanding that they continue to exist even when not perceived directly. Object Permanence is critical for building a model of the world, since…

Computer Vision and Pattern Recognition · Computer Science 2020-07-17 Aviv Shamsian , Ofri Kleinfeld , Amir Globerson , Gal Chechik