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

[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

  • depth-estimation
  • image-synthesis
  • metric-depth-estimation
  • monocular-depth-estimation

pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.

  • 3d-reconstruction
  • depth-prediction
  • feature-matching
  • global-features

[CVPR 2024 - Oral, Best Paper Award Candidate] Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation

  • monocular-depth-estimation
  • diffusion
  • in-the-wild
  • zero-shot

[CVPR'25 Oral] MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision

  • 3d-reconstruction
  • 3d-vision
  • monocular-depth-estimation
  • monocular-geometry-estimation

A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter.

Official implementation of Joint Monocular 3D Vehicle Detection and Tracking (ICCV 2019)

  • 3d-tracking
  • 3d-estimation
  • monocular-3d-detection
  • monocular-vehicle-tracking

Official implementation of FlowHMR, a generative model for physically plausible motion capture from monocular video.

A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social distancing, and body orientation.

  • 3d-object-detection
  • 3d-detection
  • 3d-deep-learning
  • pytorch