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Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments
Our experimental evaluation demonstrates that the result of our method is comparable to fully supervised methods on the NYU Depth V2 benchmark.
Unsupervised High-Resolution Depth Learning From Videos With Dual Networks
Unsupervised depth learning takes the appearance difference between a target view and a view synthesized from its adjacent frame as supervisory signal.
Monocular Depth Estimation
Vocal Bursts Intensity Prediction
