Rebalancing gradient to improve self-supervised co-training of depth, odometry and optical flow predictions

ArXi:2605.07945v1 Announce Type: new We present CoopNet, an approach that improves the cooperation of co-trained networks by dynamically adapting the apportionment of gradient, to ensure equitable learning progress. It is applied to motion-aware self-supervised prediction of depth maps, by