Learned image compression methods generally optimize a rate-distortion loss, trading off improvements in visual distortion for added bitrate. Increasingly, however, compressed imagery is used as an input to deep learning networks various tasks such classification, object detection, and superresolution. We propose recognition-aware learned method, which optimizes loss alongside task-specific joi...
