Historyobjectrecognition
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Filament | 15,461 |  | 2 | 4 | 20 hours ago | 93 | September 20, 2022 | 102 | apache-2.0 | C++ |
| Filament is a real-time physically based rendering engine for Android, iOS, Windows, Linux, macOS, and WebGL2 | ||||||||||
| Cgltf | 1,120 | 14 days ago | 25 | mit | C | |||||
| :diamond_shape_with_a_dot_inside: Single-file glTF 2.0 loader and writer written in C99 | ||||||||||
| Gltfast | 840 | 12 days ago | 103 | apache-2.0 | C# | |||||
| Efficient glTF 3D import / export package for Unity | ||||||||||
| Depth | 781 | 4 years ago | 1 | mit | Java | |||||
| Add some Depth to your fragments | ||||||||||
| Yave | 378 | 25 days ago | mit | C++ | ||||||
| Yet Another Vulkan Engine | ||||||||||
| Three Customshadermaterial | 339 |  | 15 | 20 days ago | 61 | November 27, 2022 | other | TypeScript | ||
| Extend Three.js standard materials with your own shaders! | ||||||||||
| Historyobjectrecognition | 288 | 6 years ago | 3 | Python | ||||||
| Dagon | 272 |  | 1 | 10 days ago | 34 | August 30, 2022 | 14 | other | D | |
| 3D game engine for D | ||||||||||
| Elm 3d Scene | 176 | 2 years ago | 2 | June 27, 2020 | 56 | mpl-2.0 | Elm | |||
| A high-level 3D rendering engine for Elm, with support for lighting, shadows, and realistic materials. | ||||||||||
| Unity Dithered Transparency Shader | 167 | 2 years ago | 1 | mit | ShaderLab | |||||
| Unity material and shader for applying clipped, dithered transparency | ||||||||||
The Modern History of Object Recognition
Object Recognition has recently become one of the most exciting fields in computer vision and AI. The ability of immediately recognizing all the objects in a scene seems to be no longer a secret of evolution. With the development of Convolutional Neural Network architectures, backed by big training data and advanced computing technology, a computer now can surpass human performance in object recognition task under some specific settings, such as face recognition. I fell like whenever such an amazing thing happens; someone must tell the story of it. That is why this infographic was born. Its mission is to tell the modern history of object recognition in the most concise and engaging way.
This infographic is made by Adobe Illustrator. Every illustrations has been redrawn to make them more consistent and understandable. Note that although I've built the 3D model for AlexNet and many materials are included in this project, I did not use it in the final infographics.
Main Files:
- HistoryOfObjectRecognition.ai: The main file, containing the whole project
- HistoryOfObjectRecognition.png: PNG output of the last version
- HistoryOfObjectRecognition.pdf: PDF output of the last version
- References.xlsx: All References and Links
Folders:
- AlexNet3DModel: a 3D sketch and some rendered images of a AlexNet 3D model
- Images: images used in the illustrator file
- Materials: materials used in AlexNet3DModel
- Outputs: collection of pdf outputs that I produced during the development of the infographics
- ReceptiveField: a side project that I have done before this project to help me understand and calculate the ReceptiveField
- References: references that I follow to build up the infographics
- Textures: textures used in AlexNet3DModel
