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The data storage has been one of the bottlenecks in surveillance systems. The conventional video compression algorithms such as H.264 and H.265 do not fully utilize the low information density characteristic of the surveillance video. In…

Computer Vision and Pattern Recognition · Computer Science 2020-09-29 Lirong Wu , Kejie Huang , Haibin Shen , Lianli Gao

Localizing stereo boundaries and predicting nearby disparities are difficult because stereo boundaries induce occluded regions where matching cues are absent. Most modern computer vision algorithms treat occlusions secondarily (e.g., via…

Computer Vision and Pattern Recognition · Computer Science 2021-09-09 Jialiang Wang , Todd Zickler

Images captured in participating media such as murky water, fog, or smoke are degraded by scattered light. Thus, the use of traditional three-dimensional (3D) reconstruction techniques in such environments is difficult. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2018-04-11 Yuki Fujimura , Masaaki Iiyama , Atsushi Hashimoto , Michihiko Minoh

We introduce a novel architecture for neural disparity refinement aimed at facilitating deployment of 3D computer vision on cheap and widespread consumer devices, such as mobile phones. Our approach relies on a continuous formulation that…

Computer Vision and Pattern Recognition · Computer Science 2021-11-01 Filippo Aleotti , Fabio Tosi , Pierluigi Zama Ramirez , Matteo Poggi , Samuele Salti , Stefano Mattoccia , Luigi Di Stefano

Recent advances in photographic sensing technologies have made it possible to achieve light detection in terms of a single photon. Photon counting sensors are being increasingly used in many diverse applications. We address the problem of…

Computer Vision and Pattern Recognition · Computer Science 2019-05-14 Paramanand Chandramouli , Samuel Burri , Claudio Bruschini , Edoardo Charbon , Andreas Kolb

Image de-fencing is one of the important aspects of recreational photography in which the objective is to remove the fence texture present in an image and generate an aesthetically pleasing version of the same image without the fence…

Computer Vision and Pattern Recognition · Computer Science 2019-08-20 Divyanshu Gupta , Shorya Jain , Utkarsh Tripathi , Pratik Chattopadhyay , Lipo Wang

In this paper, we propose a new model to segment cells in phase contrast microscopy images. Cell images collected from the similar scenario share a similar background. Inspired by this, we separate cells from the background in images by…

Computer Vision and Pattern Recognition · Computer Science 2019-04-02 Lin Zhang

Video Denoising is one of the fundamental tasks of any videoprocessing pipeline. It is different from image denoising due to the tem-poral aspects of video frames, and any image denoising approach appliedto videos will result in flickering.…

Image and Video Processing · Electrical Eng. & Systems 2020-08-28 Aryansh Omray , Samyak Jain , Utsav Krishnan , Pratik Chattopadhyay

To evaluate their performance, existing dehazing approaches generally rely on distance measures between the generated image and its corresponding ground truth. Despite its ability to produce visually good images, using pixel-based or even…

Computer Vision and Pattern Recognition · Computer Science 2020-02-10 Sébastien de Blois , Ihsen Hedhli , Christian Gagné

Compared to DSLR cameras, smartphone cameras have smaller sensors, which limits their spatial resolution; smaller apertures, which limits their light gathering ability; and smaller pixels, which reduces their signal-to noise ratio. The use…

Computer Vision and Pattern Recognition · Computer Science 2021-02-18 Bartlomiej Wronski , Ignacio Garcia-Dorado , Manfred Ernst , Damien Kelly , Michael Krainin , Chia-Kai Liang , Marc Levoy , Peyman Milanfar

Rain streaks will inevitably be captured by some outdoor vision systems, which lowers the image visual quality and also interferes various computer vision applications. We present a novel rain removal method in this paper, which consists of…

Computer Vision and Pattern Recognition · Computer Science 2018-12-21 Yinglong Wang , Shuaicheng Liu , Chen Chen , Dehua Xie , Bing Zeng

The ability to identify the static background in videos captured by a moving camera is an important pre-requisite for many video applications (e.g. video stabilization, stitching, and segmentation). Existing methods usually face…

Computer Vision and Pattern Recognition · Computer Science 2019-03-07 Kaimo Lin , Nianjuan Jiang , Loong Fah Cheong , Jiangbo Lu , Xun Xu

We present the first method capable of photorealistically reconstructing deformable scenes using photos/videos captured casually from mobile phones. Our approach augments neural radiance fields (NeRF) by optimizing an additional continuous…

Computer Vision and Pattern Recognition · Computer Science 2021-09-13 Keunhong Park , Utkarsh Sinha , Jonathan T. Barron , Sofien Bouaziz , Dan B Goldman , Steven M. Seitz , Ricardo Martin-Brualla

By analyzing the motion of people and other objects in a scene, we demonstrate how to infer depth, occlusion, lighting, and shadow information from video taken from a single camera viewpoint. This information is then used to composite new…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Yifan Wang , Brian Curless , Steve Seitz

Hand pose estimation from the monocular 2D image is challenging due to the variation in lighting, appearance, and background. While some success has been achieved using deep neural networks, they typically require collecting a large dataset…

Computer Vision and Pattern Recognition · Computer Science 2019-04-17 Yikang Li , Chris Twigg , Yuting Ye , Lingling Tao , Xiaogang Wang

We propose a Spatiotemporal Sampling Network (STSN) that uses deformable convolutions across time for object detection in videos. Our STSN performs object detection in a video frame by learning to spatially sample features from the adjacent…

Computer Vision and Pattern Recognition · Computer Science 2018-07-25 Gedas Bertasius , Lorenzo Torresani , Jianbo Shi

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

In this paper, an automatic method is proposed to perform image registration in visible and infrared pair of video sequences for multiple targets. In multimodal image analysis like image fusion systems, color and IR sensors are placed close…

Computer Vision and Pattern Recognition · Computer Science 2014-03-18 Tanushri Chakravorty , Guillaume-Alexandre Bilodeau , Eric Granger

Size uniformity is one of the main criteria of superpixel methods. But size uniformity rarely conforms to the varying content of an image. The chosen size of the superpixels therefore represents a compromise - how to obtain the fewest…

Computer Vision and Pattern Recognition · Computer Science 2016-11-29 Radhakrishna Achanta , Pablo Márquez-Neila , Pascal Fua , Sabine Süsstrunk

In general, background subtraction-based methods are used to detect moving objects in visual tracking applications. In this paper, we employed a background subtraction-based scheme to detect the temporarily stationary objects. We proposed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Deepak Ghimire , Joonwhoan Lee
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