MonoDVPS: A Self-Supervised Monocular Depth Estimation Approach to Depth-aware Video Panoptic Segmentation

no code implementations • 14 Oct 2022 • Andra Petrovai, Sergiu Nedevschi

Depth-aware video panoptic segmentation tackles the inverse projection problem of restoring panoptic 3D point clouds from video sequences, where the 3D points are augmented with semantic classes and temporally consistent instance identifiers.

Depth-aware Video Panoptic Segmentation Depth Prediction +4

Time-Space Transformers for Video Panoptic Segmentation

no code implementations • 7 Oct 2022 • Andra Petrovai, Sergiu Nedevschi

We propose a novel solution for the task of video panoptic segmentation, that simultaneously predicts pixel-level semantic and instance segmentation and generates clip-level instance tracks.

Instance Segmentation Segmentation +1

Exploiting Pseudo Labels in a Self-Supervised Learning Framework for Improved Monocular Depth Estimation

no code implementations • CVPR 2022 • Andra Petrovai, Sergiu Nedevschi

To improve the performance of our estimates, in the second step, we re-train the network with the scale invariant logarithmic loss supervised by pseudo labels.

Monocular Depth Estimation Self-Supervised Learning