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Related papers: Handheld Mobile Photography in Very Low Light

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While the human eye can perceive an impressive twenty stops of dynamic range, smartphone camera sensors remain limited to about twelve stops despite decades of research. A variety of high dynamic range (HDR) image capture and processing…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Baiang Li , Ruyu Yan , Ethan Tseng , Zhoutong Zhang , Adam Finkelstein , Jiawen Chen , Felix Heide

Low-light optical imaging refers to the use of cameras to capture images with minimal photon flux. This area has broad application to diverse fields, including optical microscopy for biological studies. In such studies, it is important to…

We study human pose estimation in extremely low-light images. This task is challenging due to the difficulty of collecting real low-light images with accurate labels, and severely corrupted inputs that degrade prediction quality…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Sohyun Lee , Jaesung Rim , Boseung Jeong , Geonu Kim , Byungju Woo , Haechan Lee , Sunghyun Cho , Suha Kwak

Imaging in low light is extremely challenging due to low photon counts. Using sensitive CMOS cameras, it is currently possible to take videos at night under moonlight (0.05-0.3 lux illumination). In this paper, we demonstrate photorealistic…

Computer Vision and Pattern Recognition · Computer Science 2022-04-11 Kristina Monakhova , Stephan R. Richter , Laura Waller , Vladlen Koltun

Images acquired by computer vision systems under low light conditions have multiple characteristics like high noise, lousy illumination, reflectance, and bad contrast, which make object detection tasks difficult. Much work has been done to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-02 Winston Chen , Tejas Shah

Low-light-level imaging techniques have application in many diverse fields, ranging from biological sciences to security. We demonstrate a single-photon imaging system based on a time-gated inten- sified CCD (ICCD) camera in which the image…

Scene reconstruction in the presence of high-speed motion and low illumination is important in many applications such as augmented and virtual reality, drone navigation, and autonomous robotics. Traditional motion estimation techniques fail…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Sacha Jungerman , Atul Ingle , Mohit Gupta

This paper considers matching images of low-light scenes, aiming to widen the frontier of SfM and visual SLAM applications. Recent image sensors can record the brightness of scenes with more than eight-bit precision, available in their…

Computer Vision and Pattern Recognition · Computer Science 2021-09-15 Wenzheng Song , Masanori Suganuma , Xing Liu , Noriyuki Shimobayashi , Daisuke Maruta , Takayuki Okatani

3D photography is a new medium that allows viewers to more fully experience a captured moment. In this work, we refer to a 3D photo as one that displays parallax induced by moving the viewpoint (as opposed to a stereo pair with a fixed…

Low-light imaging with handheld mobile devices is a challenging issue. Limited by the existing models and training data, most existing methods cannot be effectively applied in real scenarios. In this paper, we propose a new low-light image…

Image and Video Processing · Electrical Eng. & Systems 2021-03-02 Meng Chang , Huajun Feng , Zhihai Xu , Qi Li

We experimentally demonstrate an imaging technique based on quantum noise modification after interaction with an opaque object. By using a homodyne-like detection scheme, we eliminate the detrimental effect of the camera's dark noise,…

Photographs captured by smartphones and mid-range cameras have limited spatial resolution and dynamic range, with noisy response in underexposed regions and color artefacts in saturated areas. This paper introduces the first approach (to…

Computer Vision and Pattern Recognition · Computer Science 2022-08-01 Bruno Lecouat , Thomas Eboli , Jean Ponce , Julien Mairal

Images captured under extremely low light conditions are noise-limited, which can cause existing robotic vision algorithms to fail. In this paper we develop an image processing technique for aiding 3D reconstruction from images acquired in…

Robotics · Computer Science 2021-08-24 Ahalya Ravendran , Mitch Bryson , Donald G. Dansereau

We present a method for harmonizing the lighting of a foreground video to match a target background scene, adjusting shadows, color tone, and illumination intensity (relightful harmonization). Unlike images, acquiring labeled data for…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Jun Myeong Choi , Jae Shin Yoon , Luchao Qi , Roni Sengupta , Joon-Young Lee

When dynamic objects are captured by a camera, motion blur inevitably occurs. Such a blur is sometimes considered as just a noise, however, it sometimes gives an important effect to add dynamism in the scene for photographs or videos.…

Computer Vision and Pattern Recognition · Computer Science 2021-09-23 Michihiro Mikamo , Ryo Furukawa , Hiroshi Kawasaki

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

Shallow depth-of-field is commonly used by photographers to isolate a subject from a distracting background. However, standard cell phone cameras cannot produce such images optically, as their short focal lengths and small apertures capture…

Computer Vision and Pattern Recognition · Computer Science 2018-06-13 Neal Wadhwa , Rahul Garg , David E. Jacobs , Bryan E. Feldman , Nori Kanazawa , Robert Carroll , Yair Movshovitz-Attias , Jonathan T. Barron , Yael Pritch , Marc Levoy

We present a learning-based method to infer plausible high dynamic range (HDR), omnidirectional illumination given an unconstrained, low dynamic range (LDR) image from a mobile phone camera with a limited field of view (FOV). For training…

Computer Vision and Pattern Recognition · Computer Science 2019-04-03 Chloe LeGendre , Wan-Chun Ma , Graham Fyffe , John Flynn , Laurent Charbonnel , Jay Busch , Paul Debevec

In this paper, we study the problem of making brighter images from dark images found in the wild. The images are dark because they are taken in dim environments. They suffer from color shifts caused by quantization and from sensor noise. We…

Computer Vision and Pattern Recognition · Computer Science 2022-05-19 Sara Aghajanzadeh , David Forsyth

Long exposure photography produces stunning imagery, representing moving elements in a scene with motion-blur. It is generally employed in two modalities, producing either a foreground or a background blur effect. Foreground blur images are…

Computer Vision and Pattern Recognition · Computer Science 2023-08-04 Eric Tabellion , Nikhil Karnad , Noa Glaser , Ben Weiss , David E. Jacobs , Yael Pritch
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