Fully Convolutional Instance-aware Semantic Segmentation
2016-11-23CVPR 2017Code Available2· sign in to hype
Yi Li, Haozhi Qi, Jifeng Dai, Xiangyang Ji, Yichen Wei
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/daijifeng001/TA-FCNOfficialIn papermxnet★ 0
- github.com/divamgupta/image-segmentation-kerastf★ 3,004
- github.com/msracver/FCISmxnet★ 0
Abstract
We present the first fully convolutional end-to-end solution for instance-aware semantic segmentation task. It inherits all the merits of FCNs for semantic segmentation and instance mask proposal. It performs instance mask prediction and classification jointly. The underlying convolutional representation is fully shared between the two sub-tasks, as well as between all regions of interest. The proposed network is highly integrated and achieves state-of-the-art performance in both accuracy and efficiency. It wins the COCO 2016 segmentation competition by a large margin. Code would be released at https://github.com/daijifeng001/TA-FCN.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| COCO test-dev | FCIS+++ +OHEM | mask AP | 33.6 | — | Unverified |
| COCO test-dev | FCIS +OHEM | mask AP | 29.2 | — | Unverified |