multi-task model can help to improve model accuracy when there is few data.
some papers show good results for joint semantic segmentation and depth prediction task.
is this a valid solution for Scene Understanding for Autonomous Drone SUADD 2023?
Note: this will use both depth and label data for each competition.
can we use depth data to generate novel view synthesis for segmentation training? (e.g. can we cross use the data of different task?)