Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/Zhou et al

Zhou et al

Reported on 10 benchmarks across 2 tasks · 1 paper · 10 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision5 results

Depth EstimationonNYU-Depth V2 self-supervised
Absolute relative error (AbsRel)· 2019-10-20
0.208
best: 0.126 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898
Depth EstimationonNYU-Depth V2 self-supervised
Root mean square error (RMSE)· 2019-10-20
0.712
best: 0.494 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898
Depth EstimationonNYU-Depth V2 self-supervised
delta_1· 2019-10-20
67.4
best: 84.5 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898
Depth EstimationonNYU-Depth V2 self-supervised
delta_2· 2019-10-20
90
best: 96.5 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898
Depth EstimationonNYU-Depth V2 self-supervised
delta_3· 2019-10-20
96.8
best: 99.1 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898

Methodology5 results

3DonNYU-Depth V2 self-supervised
Absolute relative error (AbsRel)· 2019-10-20
0.208
best: 0.126 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898
3DonNYU-Depth V2 self-supervised
Root mean square error (RMSE)· 2019-10-20
0.712
best: 0.494 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898
3DonNYU-Depth V2 self-supervised
delta_1· 2019-10-20
67.4
best: 84.5 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898
3DonNYU-Depth V2 self-supervised
delta_2· 2019-10-20
90
best: 96.5 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898
3DonNYU-Depth V2 self-supervised
delta_3· 2019-10-20
96.8
best: 99.1 (IndoorDepth)
SOTA
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments arXiv:1910.08898