4.3k citations · 10.2k across the 23 of their papers we have counts for
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Loss is its own Reward: Self-Supervision for Reinforcement Learning
Evan Shelhamer, Parsa Mahmoudieh, Max Argus +1
Reinforcement learning optimizes policies for expected cumulative reward. Need the supervision be so narrow? Reward is delayed and sparse for many tasks, making it a difficult and…
Clockwork Convnets for Video Semantic Segmentation
Evan Shelhamer, Kate Rakelly, Judy Hoffman +1
Recent years have seen tremendous progress in still-image segmentation; however the naïve application of these state-of-the-art algorithms to every video frame requires considerabl…
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer, Jonathan Long, Trevor Darrell
Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, impro…