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intelligentmachineslab
- Lahore, Pakistan
- https://usamahasan.github.io/
- @usamahasan98
Stars
CamOdoCal: Automatic Intrinsic and Extrinsic Calibration of a Rig with Multiple Generic Cameras and Odometry
[PAMI 2022, CVPR 2023] ASH: Parallel Spatial Hashing for Fast Scene Reconstruction
APD-MVS is a MVS method which adopts adaptive patch deformation and an NCC-based matching metric.
Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"
Official code for CVPR 2023 Paper, HexPlane: A Fast Representation for Dynamic Scenes
Official PyTorch Implementation of the CVPR23 Paper "DINER: Depth-aware Image-based NEural Radiance fields"
Algorithm to texture 3D reconstructions from multi-view stereo images
Reflectance Adaptive Filtering Improves Intrinsic Image Estimation
Small Python utility to compare and visualize the output of various stereo depth estimation algorithms
PhyCV: The First Physics-inspired Computer Vision Library
[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"
[CVPR 2023 Highlight] Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars
Pythonic AI generation of images and videos
Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives: https://nvlabs.github.io/instant-ngp/
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Mesh triangle reduction using quadrics
This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"
C++ libraries and programs demonstrating mesh processing research published in ACM SIGGRAPH (1992-2003)
Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition - NeurIPS2021
NeRD: Neural Reflectance Decomposition from Image Collections - ICCV 2021
Official code for the CVPR 2022 (oral) paper "Extracting Triangular 3D Models, Materials, and Lighting From Images".
Learning Deformable Tetrahedral Meshes for 3D Reconstruction (NeurIPS 2020)
An easy-to-use Python library for processing and manipulating 3D point clouds and meshes.
Efficient Point Cloud Upsampling and Normal Estimation using Deep Learning for Robust Surface Reconstruction
Orientation aware object detection with applications to firearms