object detection in videos with tubelet proposal...

Object Detection in Videos with Tubelet Proposal Networks

Proposals in Video Object Detection Tubelet Proposal Networks Qualitative Results

Framework

Encoder-decoder LSTM

YouTube-Objects DatasetExperimental Settings

Kai Kang1, Hongsheng Li1, Tong Xiao1, Wanli Ouyang1,4, Junjie Yan2, Xihui Liu3, Xiaogang Wang11The Chinese University of Hong Kong, 2SenseTime Group Limited

3Tsinghua University, 4The University of Sydney

Results on ImageNet VID Dataset

Frames

Per-frame staticproposals

Regression to GT Boxes(RegressBox)

Regression toGT Movement

(RegressMove, Ours)

t

y

x

Tubelet Proposal Network

Motion Prediction EncoderLSTM

DecoderLSTM

ClassLabel

TubeletFeatures

Tubelet Proposal Network Encoder-decoder LSTM

ClassificationCNN

Spatial Anchors t

y

x

TubeletCNN

Tubelet GenerationA

B

A A A A

B

B

B

B

4

2f

16

5f

W2

b2

W5

b5

Block Initialization

Iter 1Iter 2

Iter 3Iter 4

Iter 5

l

Parallel Generation

Class Label

Decoder LSTM

Encoder LSTM

Tubelet Features

Object localization on YouTube-Objects (YTO) dataset

Qualitative results on ImageNet VID validation set

Results on ImageNet VID validation set

Initialization of tubelet proposal networks