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A versatile video depth estimation model should (1) be accurate and consistent across frames, (2) produce high-resolution depth maps, and (3) support real-time streaming. We propose FlashDepth, a method that satisfies all three…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Gene Chou , Wenqi Xian , Guandao Yang , Mohamed Abdelfattah , Bharath Hariharan , Noah Snavely , Ning Yu , Paul Debevec

We address the problem of estimating depth with multi modal audio visual data. Inspired by the ability of animals, such as bats and dolphins, to infer distance of objects with echolocation, some recent methods have utilized echoes for depth…

Computer Vision and Pattern Recognition · Computer Science 2021-04-06 Kranti Kumar Parida , Siddharth Srivastava , Gaurav Sharma

Depth (disparity) estimation from 4D Light Field (LF) images has been a research topic for the last couple of years. Most studies have focused on depth estimation from static 4D LF images while not considering temporal information, i.e., LF…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Takahiro Kinoshita , Satoshi Ono

Advances in neural networks enable tackling complex computer vision tasks such as depth estimation of outdoor scenes at unprecedented accuracy. Promising research has been done on depth estimation. However, current efforts are…

Computer Vision and Pattern Recognition · Computer Science 2022-11-22 Fatemeh Karimi , Amir Mehrpanah , Reza Rawassizadeh

As demand for advanced photographic applications on hand-held devices grows, these electronics require the capture of high quality depth. However, under low-light conditions, most devices still suffer from low imaging quality and inaccurate…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Sunghoon Im , Hae-Gon Jeon , In So Kweon

Depth estimation and 3D reconstruction have been extensively studied as core topics in computer vision. Starting from rigid objects with relatively simple geometric shapes, such as vehicles, the research has expanded to address general…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Muhammad Aamir , Naoya Muramatsu , Sangyun Shin , Matthew Wijers , Jia-Xing Zhong , Xinyu Hou , Amir Patel , Andrew Loveridge , Andrew Markham

Estimating the distance to objects is crucial for autonomous vehicles when using depth sensors is not possible. In this case, the distance has to be estimated from on-board mounted RGB cameras, which is a complex task especially in…

Computer Vision and Pattern Recognition · Computer Science 2022-07-04 Michaël Fonder , Damien Ernst , Marc Van Droogenbroeck

In this research, we propose a new 3D object detector with a trustworthy depth estimation, dubbed BEVDepth, for camera-based Bird's-Eye-View (BEV) 3D object detection. Our work is based on a key observation -- depth estimation in recent…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Yinhao Li , Zheng Ge , Guanyi Yu , Jinrong Yang , Zengran Wang , Yukang Shi , Jianjian Sun , Zeming Li

Fisheye cameras are increasingly adopted in robotics for near-field manipulation, navigation, and immersive perception, yet indoor depth benchmarks with accurate ground truth are still missing. To address this, we introduce WideDepth - the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Ilia Indyk , Ignat Penshin , Ivan Sosin , Maxim Monastyrny , Aleksei Valenkov , Ilya Makarov

We present an algorithm to estimate depth in dynamic video scenes. We propose to learn and infer depth in videos from appearance, motion, occlusion boundaries, and geometric context of the scene. Using our method, depth can be estimated…

Computer Vision and Pattern Recognition · Computer Science 2015-10-27 S. Hussain Raza , Omar Javed , Aveek Das , Harpreet Sawhney , Hui Cheng , Irfan Essa

Indirect Time-of-Flight (I-ToF) imaging is a widespread way of depth estimation for mobile devices due to its small size and affordable price. Previous works have mainly focused on quality improvement for I-ToF imaging especially curing the…

Computer Vision and Pattern Recognition · Computer Science 2022-06-17 HyunJun Jung , Nikolas Brasch , Ales Leonardis , Nassir Navab , Benjamin Busam

Depth cues are known to be useful for visual perception. However, direct measurement of depth is often impracticable. Fortunately, though, modern learning-based methods offer promising depth maps by inference in the wild. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Zongwei Wu , Danda Pani Paudel , Deng-Ping Fan , Jingjing Wang , Shuo Wang , Cédric Demonceaux , Radu Timofte , Luc Van Gool

Depth estimation is critical in autonomous driving for interpreting 3D scenes accurately. Recently, radar-camera depth estimation has become of sufficient interest due to the robustness and low-cost properties of radar. Thus, this paper…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Huawei Sun , Hao Feng , Julius Ott , Lorenzo Servadei , Robert Wille

Depth estimation is of critical interest for scene understanding and accurate 3D reconstruction. Most recent approaches in depth estimation with deep learning exploit geometrical structures of standard sharp images to predict corresponding…

Computer Vision and Pattern Recognition · Computer Science 2018-09-07 Marcela Carvalho , Bertrand Le Saux , Pauline Trouvé-Peloux , Andrés Almansa , Frédéric Champagnat

Estimating surface reflectance (BRDF) is one key component for complete 3D scene capture, with wide applications in virtual reality, augmented reality, and human computer interaction. Prior work is either limited to controlled environments…

Computer Vision and Pattern Recognition · Computer Science 2018-04-03 Kihwan Kim , Jinwei Gu , Stephen Tyree , Pavlo Molchanov , Matthias Nießner , Jan Kautz

Self-supervised depth estimation from monocular cameras in diverse outdoor conditions, such as daytime, rain, and nighttime, is challenging due to the difficulty of learning universal representations and the severe lack of labeled…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Weilong Yan , Ming Li , Haipeng Li , Shuwei Shao , Robby T. Tan

For better photography, most recent commercial cameras including smartphones have either adopted large-aperture lens to collect more light or used a burst mode to take multiple images within short times. These interesting features lead us…

Computer Vision and Pattern Recognition · Computer Science 2022-10-03 Changyeon Won , Hae-Gon Jeon

Video deblurring aims at recovering sharp details from a sequence of blurry frames. Despite the proliferation of depth sensors in mobile phones and the potential of depth information to guide deblurring, depth-aware deblurring has received…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 German F. Torres , Jussi Kalliola , Soumya Tripathy , Erman Acar , Joni-Kristian Kämäräinen

Omnidirectional depth sensing has its advantage over the conventional stereo systems since it enables us to recognize the objects of interest in all directions without any blind regions. In this paper, we propose a novel wide-baseline…

Computer Vision and Pattern Recognition · Computer Science 2019-08-19 Changhee Won , Jongbin Ryu , Jongwoo Lim

This paper focuses on perceiving and navigating 3D environments using echoes and RGB image. In particular, we perform depth estimation by fusing RGB image with echoes, received from multiple orientations. Unlike previous works, we go beyond…

Computer Vision and Pattern Recognition · Computer Science 2024-02-12 Lingyu Zhu , Esa Rahtu , Hang Zhao
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