[IROS24] Offical Code for "FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework" - Inegrated into Nerfstudio
- Updated
Jun 13, 2025 - Python
[IROS24] Offical Code for "FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework" - Inegrated into Nerfstudio
Official implementation for Tetra-NeRF paper - NeRF represented as triangulation of input point cloud.
[ECCV 2024] "BAD-Gaussians: Bundle Adjusted Deblur Gaussian Splatting". ⚡Train a scene from real-world blurry images in minutes!
Codebase for the WayveScenes101 Dataset
[ICRA 2024] Lightning NeRF: Efficient Hybrid Scene Representation for Autonomous Driving
3D Gaussian Splatting (3DGS) extension for Omniverse
3DGS-based change detection for physical object rearrangement
(Advanced Engineering Informatics 2025) ThermoNeRF - Thermographic NeRF
Neural Radiance Field (NeRF) extension for Omniverse
[ICLR 2025] NeRAF jointly learns acoustic and radiance fields, enabling realistic audio-visual generation.
Dive into cutting-edge FusionSLAM, where SuperPoint, SuperGlue, Neural Depth Estimation, and Instant-NGP converge, elevating Monocular SLAM to unparalleled precision and performance. Redefining mapping, localization, and reconstruction in a single camera setup.
XLD: A Cross-Lane Dataset for Benchmarking Novel Driving View Synthesis
3D reconstruction from Meta Quest passthrough and depth via Reality Capture app, with Open3D/TSDF, COLMAP/Nerfstudio export, and Gaussian Splatting prep.
⚡Accelerated nerfstudio implementation of 😈 BAD-NeRF (CVPR 2023). Train a scene from blurry images in minutes!
3D Gaussian Splatting SAM
Nerfstudio Implementation of RENI++: A Rotation-Equivariant, Scale-Invariant, Natural Illumination Prior
Style-NeRF2NeRF implementation.
This project delves into NeRF basics, such as ray tracing, ray casting, and ray marching. It starts with a simple task of reconstructing a red sphere in 3D. Then, we create a custom 3D model in Blender and take images to reconstruct the model using NeRF built from scratch and train for 7 hours!
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