Category Archives: Lab Meeting

Deep object detection – Reading session

by Zhiming Luo

InsideImagenet

  1. R-CNN

Girshick et al. “Rich feature hierarchies for accurate object detection and semantic segmentation.” CVPR. 2014.

  1. SPP-Net

He et al. “Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition.” TPAMI. 2015.

  1. Fast RCNN, OHEM

Girshick. “Fast R-CNN.” ICCV. 2015.

Shrivastava et al. “Training Region-based Object Detectors with Online Hard Example Mining.” CVPR. 2016.

  1. Faster RCNN:

Ren et al. “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.” NIPS. 2015.

Zhang et al. “Is Faster R-CNN Doing Well for Pedestrian Detection.” ECCV. 2016.

  1. YOLO, SSD

Redmon et al. “You Only Look Once: Unified, Real-Time Object Detection.” CVPR. 2016.

Liu et al. “SSD: Single Shot MultiBox Detector.” ECCV. 2016.

parallel

Python Multiprocessing

Introduction by Martin:

This Friday’s reading group will be a hands-on tutorial on multiprocessing in Python. Please make sure to have Python 2 installed on your laptop. No further preparation needed, if you want an IDE: Spyder is decent. Slides.

Topics discussed:

  • CPU count
  • Process class
  • Queues
  • Locks
  • Pool class
  • Hands-on challenge!
rnn

Recurrent Neural Network and LSTMs

A different formula will be attempted for this reading group: everyone shall each study their own paper on the subject of Recurrent Neural Networks (RNN) or Long Short-Term Memory (LSTM), and present it.

List of the available papers

Presented papers: