fferroni

fferroni's Stars

• facebookresearch/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.

  Language:Jupyter Notebook46.9k3056625.6k

• milvus-io/milvus

  A cloud-native vector database, storage for next generation AI applications

  Language:Go29.7k27611.8k2.8k

• aleju/imgaug

  Image augmentation for machine learning experiments.

  Language:Python14.4k2295152.4k

• numba/numba

  NumPy aware dynamic Python compiler using LLVM

  Language:Python9.8k1995.2k1.1k

• raulmur/ORB_SLAM2

  Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

  Language:C++9.3k3739654.7k

• tensorflow/swift

  Swift for TensorFlow

  Language:Jupyter Notebook6.1k259254608

• tensorflow/probability

  Probabilistic reasoning and statistical analysis in TensorFlow

  Language:Jupyter Notebook4.2k1631.4k1.1k

• lancedb/lance

  Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, with more integrations coming..

  Language:Rust3.8k43974212

• NVlabs/tiny-cuda-nn

  Lightning fast C++/CUDA neural network framework

  Language:C++3.7k49386449

• waymo-research/waymo-open-dataset

  Waymo Open Dataset

  Language:Python2.7k72817609

• hku-mars/FAST_LIO

  A computationally efficient and robust LiDAR-inertial odometry (LIO) package

  Language:C++2.6k52326878

• wjakob/nanobind

  nanobind: tiny and efficient C++/Python bindings

  Language:C++2.3k41172191

• JakobEngel/dso

  Direct Sparse Odometry

  Language:C++2.3k116232907

• dmlc/decord

  An efficient video loader for deep learning with smart shuffling that's super easy to digest

  Language:C++1.8k29254160

• PRBonn/kiss-icp

  A LiDAR odometry pipeline that just works

  Language:C++1.5k41204312

• bermanmaxim/LovaszSoftmax

  Code for the Lovász-Softmax loss (CVPR 2018)

  Language:Jupyter Notebook1.4k3234269

• ShuLiu1993/PANet

  PANet for Instance Segmentation and Object Detection

  Language:Python1.3k2766280

• microsoft/SoM

  Set-of-Mark Prompting for GPT-4V and LMMs

  Language:Python1.1k213586

• PRBonn/lidar-bonnetal

  Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving

  Language:Python94328110205

• nv-tlabs/GSCNN

  Gated-Shape CNN for Semantic Segmentation (ICCV 2019)

  Language:Python9163686200

• NVlabs/RADIO

  Official repository for "AM-RADIO: Reduce All Domains Into One"

  Language:Python629253423

• gisbi-kim/FAST_LIO_SLAM

  LiDAR SLAM = FAST-LIO + Scan Context

  Language:C++49483774

• NVIDIA/NeMo-Curator

  Scalable data pre processing and curation toolkit for LLMs

  Language:Jupyter Notebook477149857

• hturki/suds

  Scalable Urban Dynamic Scenes

  Language:Python19854716

• internet-explorer-ssl/internet-explorer

  Internet Explorer explores the web in a self-supervised manner to progressively find relevant examples that improve performance on a desired target dataset.

  1631846

• melfm/avod-ssd

  Code for 3D single stage object detection for autonomous driving

  Language:Python9971022

• WHU-USI3DV/WHU-Railway3D

  A large-scale benchmark dataset for railway point cloud semantic segmentation.

  Language:Python971342

• janisgp/Sampling-free-Epistemic-Uncertainty

  Code for the ICCV 2019 paper "Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation"

  Language:Jupyter Notebook92659

• pawelswoboda/RAMA

  Language:Cuda7841314

• ToyotaResearchInstitute/superdepth

  SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation

  181010