Mirlan Karimov's repositories
awesome-dinov2-extensions
This repo contains extensions to DINO V2 model by Meta, and awesome applications built on top of it.
segment_anything_streamlit_webui
This is a streamlit web interface for the Segment Anything.
academicpages.github.io
GitHub Pages template for academic personal websites.
bundle-adjusting-NeRF
BARF: Bundle-Adjusting Neural Radiance Fields š¤® (ICCV 2021 oral)
cvml_project
Projects and application using computer vision and machine learning
gameoffeats
Analysis of image features extracted via different DL-based methods for Game Theory based unsupervised saliency detection
gaussian-splatting-mask
Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"
GroundingDINO
The official implementation of "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
gtsam
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
Ha-NeRF
Ha-NeRF (Hallucinated Neural Radiance Fields in the Wild) using pytorch.
meta-sam-demo
Meta's Segment Anything Model (SAM) Demo Site
mirlansmind
Config files for my GitHub profile.
multinerf
A Code Release for Mip-NeRF 360, Ref-NeRF, and RawNeRF
NeRF-Factory
An awesome PyTorch NeRF library
nerf-pytorch
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
nerf_pl
NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
nerfstudio
A collaboration friendly studio for NeRFs
nonrigid_nerf
Open source repository for the code accompanying the paper 'Non-Rigid Neural Radiance Fields Reconstruction and Novel View Synthesis of a Deforming Scene from Monocular Video'.
Objectron
Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes
sam-streamlit
Streamlit based implementation for the The Segment Anything Model (SAM) developed by Meta AI research
Segment-and-Track-Anything
An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
streamlit-drawable-canvas
Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit? Also draws lines, circles and boxes over background images for annotation.