Alternatives and similar repositories for BEV-Perception

Users that are interested in BEV-Perception are comparing it to the libraries listed below

• NVlabs / FB-BEV
  Official PyTorch implementation of FB-BEV & FB-OCC - Forward-backward view transformation for vision-centric autonomous driving perceptio…
  ☆778Updated 9 months ago
• HuaiyuanXu / 3D-Occupancy-Perception
  [Information Fusion 2025] A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion Perspective
  ☆555Updated last week
• weiyithu / SurroundOcc
  [ICCV 2023] SurroundOcc: Multi-camera 3D Occupancy Prediction for Autonomous Driving
  ☆994Updated 6 months ago
• JeffWang987 / OpenOccupancy
  [ICCV 2023] OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception
  ☆693Updated last year
• 4DVLab / Vision-Centric-BEV-Perception
  Vision-Centric BEV Perception: A Survey
  ☆732Updated 2 years ago
• aharley / simple_bev
  A Simple Baseline for BEV Perception
  ☆601Updated 2 years ago
• OpenDriveLab / OccNet
  [ICCV 2023] OccNet: Scene as Occupancy
  ☆657Updated 6 months ago
• CVPR2023-3D-Occupancy-Prediction / CVPR2023-3D-Occupancy-Prediction
  CVPR2023-Occupancy-Prediction-Challenge
  ☆858Updated 2 years ago
• Tsinghua-MARS-Lab / Occ3D
  ☆525Updated last year
• autodriving-heart / Awesome-occupancy-perception
  ☆307Updated last year
• Yzichen / FlashOCC
  ☆470Updated last year
• HorizonRobotics / Sparse4D
  ☆564Updated last year
• Sense-GVT / Fast-BEV
  Fast-BEV: A Fast and Strong Bird’s-Eye View Perception Baseline
  ☆772Updated 2 years ago
• OpenDriveLab / Birds-eye-view-Perception
  [IEEE T-PAMI 2023] Awesome BEV perception research and cookbook for all level audience in autonomous diriving
  ☆1,348Updated 5 months ago
• wzzheng / TPVFormer
  [CVPR 2023] An academic alternative to Tesla's occupancy network for autonomous driving.
  ☆1,314Updated last year
• chaytonmin / Awesome-BEV-Perception-Multi-Cameras
  Awesome papers about Multi-Camera 3D Object Detection and Segmentation in Bird's-Eye-View, such as DETR3D, BEVDet, BEVFormer, BEVDepth, U…
  ☆1,088Updated last year
• zya3d / Awesome-3D-Occupancy-Prediction
  Vision-based 3D occupancy prediction in autonomous driving: a review and outlook
  ☆256Updated last year
• OpenDriveLab / OpenLane-V2
  [NeurIPS 2023 Track Datasets and Benchmarks] OpenLane-V2: The First Perception and Reasoning Benchmark for Road Driving
  ☆650Updated 6 months ago
• Megvii-BaseDetection / BEVDepth
  Official code for BEVDepth.
  ☆838Updated 2 years ago
• exiawsh / StreamPETR
  [ICCV 2023] StreamPETR: Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection
  ☆754Updated last year
• hustvl / MapTR
  [ICLR'23 Spotlight & ECCV'24 & IJCV'24] MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction
  ☆1,437Updated 10 months ago
• hht1996ok / EA-LSS
  EA-LSS: Edge-aware Lift-splat-shot Framework for 3D BEV Object Detection
  ☆320Updated 2 years ago
• PJLab-ADG / DetZero
  [ICCV 2023] DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds
  ☆412Updated last year
• zhangyp15 / OccFormer
  [ICCV 2023] OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction
  ☆389Updated 2 years ago
• ADLab-AutoDrive / BEVFusion
  Offical PyTorch implementation of "BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework"
  ☆930Updated 2 years ago
• MCG-NJU / SparseBEV
  [ICCV 2023] SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos
  ☆446Updated last year
• linxuewu / Sparse4D
  Sparse4D v1 & v2
  ☆487Updated last year
• nv-tlabs / lift-splat-shoot
  Lift, Splat, Shoot: Encoding Images from Arbitrary Camera Rigs by Implicitly Unprojecting to 3D (ECCV 2020)
  ☆1,291Updated last year
• hustvl / VMA
  A general map auto annotation framework based on MapTR, with high flexibility in terms of spatial scale and element type
  ☆293Updated last year
• MCG-NJU / SparseOcc
  [ECCV 2024] Fully Sparse 3D Occupancy Prediction & RayIoU Evaluation Metric
  ☆389Updated last year