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State-of-the-art frame interpolation methods generate intermediate frames by inferring object motions in the image from consecutive key-frames. In the absence of additional information, first-order approximations, i.e. optical flow, must be…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Stepan Tulyakov , Daniel Gehrig , Stamatios Georgoulis , Julius Erbach , Mathias Gehrig , Yuanyou Li , Davide Scaramuzza

Event cameras respond to brightness changes in the scene asynchronously and independently for every pixel. Due to the properties, these cameras have distinct features: high dynamic range (HDR), high temporal resolution, and low power…

Computer Vision and Pattern Recognition · Computer Science 2022-10-17 Jongwan Kim , DongJin Lee , Byunggook Na , Seongsik Park , Jeonghee Jo , Sungroh Yoon

Event cameras are novel sensors that report brightness changes in the form of asynchronous "events" instead of intensity frames. They have significant advantages over conventional cameras: high temporal resolution, high dynamic range, and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-18 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

Event cameras are a kind of bio-inspired sensors that generate data when the brightness changes, which are of low-latency and high dynamic range (HDR). However, due to the nature of the sparse event stream, event-based mapping can only…

Robotics · Computer Science 2021-06-04 Yan Dong

Event cameras or dynamic vision sensors (DVS) record asynchronous response to brightness changes instead of conventional intensity frames, and feature ultra-high sensitivity at low bandwidth. The new mechanism demonstrates great advantages…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Bo Zhang , Yuqi Han , Jinli Suo , Qionghai Dai

Despite the dynamic development of computer vision algorithms, the implementation of perception and control systems for autonomous vehicles such as drones and self-driving cars still poses many challenges. A video stream captured by…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Piotr Wzorek , Tomasz Kryjak

Real-time Stereo Matching is a cornerstone algorithm for many Extended Reality (XR) applications, such as indoor 3D understanding, video pass-through, and mixed-reality games. Despite significant advancements in deep stereo methods,…

Computer Vision and Pattern Recognition · Computer Science 2023-09-11 Ziang Cheng , Jiayu Yang , Hongdong Li

Event cameras, i.e., the Dynamic and Active-pixel Vision Sensor (DAVIS) ones, capture the intensity changes in the scene and generates a stream of events in an asynchronous fashion. The output rate of such cameras can reach up to 10 million…

Computer Vision and Pattern Recognition · Computer Science 2020-10-30 Sherif A. S. Mohamed , Jawad N. Yasin , Mohammad-Hashem Haghbayan , Antonio Miele , Jukka Heikkonen , Hannu Tenhunen , Juha Plosila

Event cameras, or Dynamic Vision Sensors (DVS) are novel neuromorphic sensors that capture brightness changes as a continuous stream of "events" rather than traditional intensity frames. Converting sparse events to dense intensity frames…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Yuhan Bao , Lei Sun , Yuqin Ma , Kaiwei Wang

This paper reports a Dynamic Vision Sensor (DVS) event camera that is 6x more sensitive at 14x lower illumination than existing commercial and prototype cameras. Event cameras output a sparse stream of brightness change events. Their high…

Image and Video Processing · Electrical Eng. & Systems 2024-09-17 Rui Graca , Sheng Zhou , Brian McReynolds , Tobi Delbruck

Event cameras are innovative neuromorphic sensors that asynchronously capture the scene dynamics. Due to the event-triggering mechanism, such cameras record event streams with much shorter response latency and higher intensity sensitivity…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Yunhao Zou , Ying Fu , Tsuyoshi Takatani , Yinqiang Zheng

Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion blur and large pixel displacements. We introduce EventTrack6D,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jae-Young Kang , Hoonhee Cho , Taeyeop Lee , Minjun Kang , Bowen Wen , Youngho Kim , Kuk-Jin Yoon

Event-based cameras (ECs) have emerged as bio-inspired sensors that report pixel brightness changes asynchronously, offering unmatched speed and efficiency in vision sensing. Despite their high dynamic range, temporal resolution, low power…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Seyed Ehsan Marjani Bajestani , Giovanni Beltrame

We present StereoWorld, a camera-conditioned stereo world model that jointly learns appearance and binocular geometry for end-to-end stereo video generation.Unlike monocular RGB or RGBD approaches, StereoWorld operates exclusively within…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yang-Tian Sun , Zehuan Huang , Yifan Niu , Lin Ma , Yan-Pei Cao , Yuewen Ma , Xiaojuan Qi

Event cameras are bio-inspired dynamic vision sensors that respond to changes in image intensity with a high temporal resolution, high dynamic range and low latency. These sensor characteristics are ideally suited to enable visual target…

Robotics · Computer Science 2022-08-04 Ziwei Wang , Yonhon Ng , Jack Henderson , Robert Mahony

Event cameras are bioinspired sensors with reaction times in the order of microseconds. This property makes them appealing for use in highly-dynamic computer vision applications. In this work,we explore the limits of this sensing technology…

Computer Vision and Pattern Recognition · Computer Science 2020-10-14 William Chamorro , Juan Andrade-Cetto , Joan Solà

Once an academic venture, autonomous driving has received unparalleled corporate funding in the last decade. Still, the operating conditions of current autonomous cars are mostly restricted to ideal scenarios. This means that driving in…

Computer Vision and Pattern Recognition · Computer Science 2021-03-11 Mathias Gehrig , Willem Aarents , Daniel Gehrig , Davide Scaramuzza

Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.). Optical flow estimation methods that work on packets of events trade off speed for accuracy,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Shintaro Shiba , Yoshimitsu Aoki , Guillermo Gallego

Event cameras, with a high dynamic range exceeding $120dB$, significantly outperform traditional embedded cameras, robustly recording detailed changing information under various lighting conditions, including both low- and high-light…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Yunfan Lu , Xiaogang Xu , Hao Lu , Yanlin Qian , Pengteng Li , Huizai Yao , Bin Yang , Junyi Li , Qianyi Cai , Weiyu Guo , Hui Xiong

An event camera detects per-pixel intensity difference and produces asynchronous event stream with low latency, high dynamic range, and low power consumption. As a trade-off, the event camera has low spatial resolution. We propose an…

Computer Vision and Pattern Recognition · Computer Science 2020-04-13 S. Mohammad Mostafavi I. , Jonghyun Choi , Kuk-Jin Yoon
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