| Category | Playground | Description |
|---|---|---|
| 2D Computer Vision | Cookbooks | A collection of notebook for 2D Computer vision |
| Book_deep_learning_from_scratch_5 | Jupyter notebooks for Deep learning from Scratch 5 | |
| Book_generative_deep_learning_2nd | Jupyter notebooks for Generative Deep Learning, 2nd Eidtion | |
| TinyDiffusion | Experimental notebooks for Diffusion models | |
| HF_Transformers | Tutorial notebooks for Hugging Face Transformers | |
| HF_Diffusion | A collection of Jupyter notebooks for the Hugging Face Diffusion library. | |
| DINOv3 | Demo Jupyter notebooks for DINOv3 model | |
| Yolo | Playgrounds for YOLO models and Ultralytics's models | |
| 3D Computer Vision | Cookbooks | A collection of notebook for 3D Computer vision |
| Monocular_slam_front_end | Exploratory code for Monocular SLAM Front End | |
| TinyNeRF | Experimental notebooks for NeRF models | |
| GSPLAT | Evaluation notebooks for Gaussian Splatting methods with various datasets | |
| Triangle_splatting | Demo notebooks for Triangle Splatting with various datasets | |
| Triangle_splatting2 | Test notebooks for Triangle Splatting with custom datasets | |
| ADAS | Demo notebooks for ADAS system | |
| Docs | Study resources for 2D/3D computer Vision | |
- Paper:
- DINOv3
- NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis [arXiv]
- FastNeRF: High-Fidelity Neural Rendering at 200FPS [arXiv]
- KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs [arXiv]
- PlenOctrees for Real-time Rendering of Neural Radiance Fields [arXiv]
- Plenoxels: Radiance Fields without Neural Networks [arXiv]
- InfoNeRF: Ray Entropy Minimization for Few-Shot Neural Volume Rendering [arXiv]
- Instant Neural Graphics Primitives with a Multiresolution Hash Encoding [arXiv]
- K-Planes: Explicit Radiance Fields in Space, Time, and Appearance [arXiv]
- FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularization [arXiv]
- 3D Gaussian Splatting for Real-Time Radiance Field Rendering
- 3D Gaussian Splatting as Markov Chain Monte Carlo
- 3D Gaussian Splatting as Markov Chain Monte Carlo - NIPS papers
- 3D Gaussian Splatting as Markov Chain Monte Carlo - OpenReview
- 2D Gaussian Splatting for Geometrically Accurate Radiance Fields
- 2D Gaussian Splatting for Geometrically Accurate Radiance Fields
- Anti-Aliased 2D Gaussian Splatting
- 3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting
- Triangle Splatting for Real-Time Radiance Field Rendering
- Blog:
- Flow Matching vs Diffusion
- Hugging Face :: Transformers
- Hugging Face Diffusers
- DINOV3
- Request access to Meta DINOv3
- Training CLIP Model from Scratch for an Fashion Image Retrieval App
- Understanding CLIP for vision language models
- CLIP Model and The Importance of Multimodal Embeddings
- CLIP, Intuitively and Exhaustively Explained
- https://learnopencv.com/iterative-closest-point-icp-explained/
- https://learnopencv.com/3d-lidar-visualization/
- https://learnopencv.com/3d-lidar-object-detection/
- https://learnopencv.com/monocular-slam-in-python/
- 3D Gaussian Splatting Introduction – Paper Explanation & Training on Custom Datasets with NeRF Studio Gsplats
- gsplat documentation
- https://trianglesplatting.github.io/
- The Future of 3D Is… Triangles?!
- Github:
- Papers-in-100-Lines-of-Code
- DDPM: https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Denoising_Diffusion_Probabilistic_Models
- https://medium.com/@adityanutakki/sr3-explained-and-implemented-in-pytorch-from-scratch-b43b9742c232
- https://github.com/aditya-nutakki/pfs/tree/master/sr3
- https://github.com/CodingVillainKor/SimpleDeepLearning/blob/main/flowmatching.ipynb
- https://github.com/harshm121/Diffusion-v-FlowMatching/
- https://github.com/huggingface/transformers/tree/main/notebooks
- https://github.com/huggingface/notebooks/tree/main
- DINOv3
- https://github.com/spmallick/learnopencv/tree/master/Training-CLIP-from-Scratch-for-Image-Retrieval
- https://github.com/metamath1/pytorch-stable-diffusion-fine-tuning
- https://github.com/davidADSP/Generative_Deep_Learning_2nd_Edition
- https://github.com/oreilly-japan/deep-learning-from-scratch-5
- https://github.com/OmarJItani/Iterative-Closest-Point-Algorithm/tree/main
- https://github.com/spmallick/learnopencv/tree/master/Monocular%20SLAM%20for%20Robotics%20implementation%20in%20python
- Papers-in-100-Lines-of-Code
- gsplat
- https://github.com/trianglesplatting/triangle-splatting
- SFA3D