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Amazing! I always thought it must be a huge disadvantage that computer vision only has one frame to work with (and only one camera vs 2 eyes). Often as a human
by jonplackett 6y ago
Amazing! I always thought it must be a huge disadvantage that computer vision only has one frame to work with (and only one camera vs 2 eyes). Often as a human you stare at for a while when trying to spot something tricky, like a bird in the trees and then find it when it moves. Or you move you head side to side to create movement. It would be interesting to see a comparison with what the best single frame segmentation could detect in one of these scenes.
- deleted 6y ago[deleted]
- weidi_xie 6y agoIf you check the Table 3, you can see the comparison with some of the top unsupervised video segmentation model, trained with supervised learning, eg. COSNet, MATNet. They perform reasonably well on MoCA, but they were all trained with massive manual segmentation annotations, which is not typically not scalable. The proposed self-supervised approach is comparable to those top methods, even without using RGB, and any manual annotations.