-
Depth-Anything
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Depth estimation improved a lot as well e.g. with Depth-Anything [0]. But those are mostly relative depth instead of metric. Also when even converted to metric they still seems have a lot of pointclouds at the edges that have to be pruned - visible in this blog [1]. Looks like those models trained on Lidar or Stereo depthmaps that has this limitations. I think we don't have enough clean training data for 3d unless we maybe train on synthetic data (then we can have plenty, generate realistic scene in Unreal Engine 5 and train on rendered 2d frames)
[0] https://github.com/LiheYoung/Depth-Anything
[1] https://medium.com/@patriciogv/the-state-of-the-art-of-depth...
Related posts
-
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
-
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
-
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
-
🚀 Deep Learning for Deep Objects: ZoeDepth is an AI Model for Multi-Domain Depth Estimation
-
Testing ControlNet on Unreal Engine 5