Exploring Long-Sequence Masked Autoencoders

Shows consistent gains across various setups w/o extra compute on object detection and semantic segmentation by decoupling the mask size from the patch size.

Implementing Long-Sequence Masked Autoencoders can improve object detection and semantic segmentation without extra computation cost, providing new insights and avenues for scaling in computer vision.