103 citations · 144 across the 3 of their papers we have counts for
7 papers
SOLO: A Simple Framework for Instance Segmentation
Xinlong Wang, Rufeng Zhang, Chunhua Shen +2
Compared to many other dense prediction tasks, e.g., semantic segmentation, it is the arbitrary number of instances that has made instance segmentation much more challenging. In or…
TransTrack: Multiple Object Tracking with Transformer
Peize Sun, Jinkun Cao, Yi Jiang +5
In this work, we propose TransTrack, a simple but efficient scheme to solve the multiple object tracking problems. TransTrack leverages the transformer architecture, which is an at…
Sparse R-CNN: End-to-End Object Detection with Learnable Proposals
Peize Sun, Rufeng Zhang, Yi Jiang +8
We present Sparse R-CNN, a purely sparse method for object detection in images. Existing works on object detection heavily rely on dense object candidates, such as anchor boxes…
Dense Contrastive Learning for Self-Supervised Visual Pre-Training
Xinlong Wang, Rufeng Zhang, Chunhua Shen +2
To date, most existing self-supervised learning methods are designed and optimized for image classification. These pre-trained models can be sub-optimal for dense prediction tasks…
Mask Encoding for Single Shot Instance Segmentation
Rufeng Zhang, Zhi Tian, Chunhua Shen +2
To date, instance segmentation is dominated by twostage methods, as pioneered by Mask R-CNN. In contrast, one-stage alternatives cannot compete with Mask R-CNN in mask AP, mainly d…
SOLOv2: Dynamic and Fast Instance Segmentation
Xinlong Wang, Rufeng Zhang, Tao Kong +2
In this work, we aim at building a simple, direct, and fast instance segmentation framework with strong performance. We follow the principle of the SOLO method of Wang et al. "SOLO…