This is translated from 新智元导读

LLNet: A deep autoencoder approach to natural low-light image enhancement

The most sucessfull single stage object detection algorithms, e.g., YOLO, SSD, all relies all some anchor to refine to the final detection location. For those algorithms, the anchor are typically defined as the grid on the image coordinates at all possible locations, with different scale and aspect ratio.

Depth Map Prediction from a Single Image using a Multi-Scale Deep Network

This post is baesd on AlphaTree

In this post, we will introduce some of the most recent text detection methods. Text detection methods are highly related to object detection methods, thus could be categorized into one-stage methods and two-stage methods. Currently, two-stage methods could easily outperforms one-stage methods, e.g., using Mask-RCNN directly could give you 76% mAP on icdar2017mlt, while the current state of art methods psenet achieves 72%.

极市平台 has created a list of 45 CVPR best papers into the best paper finals. Let’s check out: