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Event-based Vision Resources

CVPR 2023 Workshop on Event-based Vision: June 19, 2023.

NeuroPAC

Table of Contents:



Survey paper

  • Gallego, G., Delbruck, T., Orchard, G., Bartolozzi, C., Taba, B., Censi, A., Leutenegger, S., Davison, A., Conradt, J., Daniilidis, K., Scaramuzza, D.,
    Event-based Vision: A Survey,
    IEEE Trans. Pattern Anal. Machine Intell. (TPAMI), 2020.

Workshops

Devices & Companies Manufacturing them

Companies working on Event-based Vision

Neuromorphic Systems

Review / Overview papers

Sensor designs, Bio-inspiration

Algorithms, Applications

Algorithms

Feature Detection and Tracking

Corner Detection and Tracking

Particle Detection and Tracking

Eye Tracking

Optical Flow Estimation

Scene Flow Estimation

Reconstruction of Visual Information

Intensity-Image Reconstruction from events

Video Synthesis

Image super-resolution

Joint/guided filtering

Tone Mapping

Visual Stabilization

Polarization Reconstruction

Depth Estimation (3D Reconstruction)

Monocular Depth Estimation

Monocular Depth Estimation using Structured Light

Monocular Object Reconstruction

Stereo Depth Estimation

Stereo Depth Estimation using Structured Light

Stereoscopic Panoramic Imaging

SLAM (Simultaneous Localization And Mapping)

Localization, Ego-Motion Estimation

Visual Servoing

Mapping

Visual Odometry / SLAM

Monocular

Stereo

Visual-Inertial Odometry

Stereo

Segmentation

Object Segmentation

Motion Segmentation

Pattern Recognition

Object Recognition

Gesture Recognition

Representation / Feature Extraction

Regression Tasks

Learning Methods / Frameworks

Signal Processing

Event Denoising

Compression

Control

Obstacle Avoidance

Space Applications

Tactile Sensing Applications

Object Pose Estimation

Human Pose Estimation

Hand Pose Estimation

Indoor Lighting Estimation

Data Encryption

Nuclear Verification

Optical Communication

Animal Behavior Monitoring

Optical Applications

Auto-focus

Speckle Analysis

Interferometry or Holography

Wavefront sensing

Optical super-resolution

Schlieren imaging



Datasets and Simulators (sorted by topic)

Emulators and Simulators

Datasets (sorted by topic)

  • Datasets from the Sensors group at INI (Institute of Neuroinformatics), Zurich:
    • DVS09 - DVS128 Dynamic Vision Sensor Silicon Retina
    • DVSFLOW16 - DVS/DAVIS Optical Flow Dataset
    • DVSACT16 - DVS Datasets for Object Tracking, Action Recognition and Object Recognition
    • PRED18 - VISUALISE Predator/Prey Dataset
    • DDD17 - DAVIS Driving Dataset 2017
    • ROSHAMBO17 - RoShamBo Rock Scissors Paper game DVS dataset
    • DHP19 - DAVIS Human Pose Estimation and Action Recognition
    • DDD20 - End-to-End Event Camera Driving Dataset
    • DND21 - DeNoising Dynamic vision sensors dataset
    • EDFLOW21 - Event Driven Flow dataset
    • MVSEC-NIGHT21 - MVSEC Nighttime Driving Labeled Cars
    • DVSD22 - Dynamic Vision Sensor Disdrometer
    • DAVIS24 - DAVIS Event Camera Sample Data

Human Pose Estimation

Stereo Depth Estimation

Monocular Object Reconstruction

Optical Flow

Intensity-Image Reconstruction from Events

Visual Odometry and SLAM

Segmentation

Recognition

Event Denoising

Space Situational Awareness

Outdoor Monitoring / Surveillance



Software

Drivers

Synchronization

  • Sync Toolbox. This open-source toolbox provides a QT-based GUI to allow easy access for hardware-level multi-sensor synchronization (Prophesee Gen 3.1 included and tested). After proper configuration of the software, users can seamlessly record new ROS bags.

Lens Calibration

Algorithms

Utilities

  • Process AEDAT: useful scripts to work with data from jAER and cAER.
  • Matlab functions in jAER project
  • AEDAT Tools: scripts for Matlab and Python to work with aedat files.
  • aedat4to2: Python/DV script to convert AEDAT4 from DV to AEDAT2 for jAER.
  • aedat4tomat: Python/DV script to convert AEDAT4 from DV to matlab file.
  • Matlab AER functions by G. Orchard. Some basic functions for filtering and displaying AER vision data, as well as making videos.
  • Python code for AER vision data by G. Orchard.
  • edvstools, by D. Weikersdorfer: A collection of tools for the embedded Dynamic Vision Sensor eDVS.
  • Tarsier Framework for event-based Vision in C++.
  • events_h52bag C++ code to convert event data from HDF5 to ROSbags.
  • events_bag2h5 Python code to convert event data from ROSbags to HDF5.
  • CelexMatlabToolbox by Yuxin Zhang. Tools to decode events generated by CeleX IV DVS, visualize them and denoise.
  • Loris Python package to read files from neuromorphic cameras.
  • Marcireau A., Ieng S.-H., Benosman R.,
    Sepia, Tarsier, and Chameleon: A Modular C++ Framework for Event-Based Computer Vision,
    Front. Neurosci. (2020), 13:1338. Code
  • BIMVEE Python tools for Batch Import, Manipulation, Visualisation and Export of Events and other timestamped data. Imports from various file formats into a common workspace format, including native Python import of rosbags.
  • Tonic provides publicly available event datasets and data transformations much like Torchvision/audio.
  • Prophesee automotive dataset toolbox, Code
  • dv_ros ROS package for accumulating event frames with iniVation Dynamic Vision System's dv-sdk.
  • dvs_event_server ROS package used to transport "dvs/events" ROS topic to Python through protobuf and zmq, because Python ROS callback has a large delay.
  • AEStream A fast C++ library with a Python interface for streaming Address Event representations directly from Inivation and Prophesee cameras to various sources, such as STDOUT, UDP (network), or PyTorch.
  • AEDAT decoder A fast AEDAT 4 Python reader, with a Rust underlying implementation.
  • aedat-rs Standalone Rust library for decoding AEDAT 4 files for use in bespoke Rust event systems.
  • expelliarmus A pip-installable Python library to decode DAT, EVT2 and EVT3 files generated by Prophesee cameras to structured NumPy arrays.
  • ADΔER A suite of tools for transcoding, inspecting, visualizing, lossy compressing, and building applications for a unified intensity event representation. Supports iniVation, Prophesee, and frame-based video sources.

Neuromorphic Processors and Platforms

Courses (Educational content)



Theses and Dissertations

Dissertations

Master's (and Bachelor's) Theses

People / Organizations

Press EETimes

Press



Contributing

Please see CONTRIBUTING for details.


Open Source Agenda is not affiliated with "Event Based Vision Resources" Project. README Source: uzh-rpg/event-based_vision_resources
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