480 citations · 1k across the 10 of their papers we have counts for
10 papers
FlowAD: Ego-Scene Interactive Modeling for Autonomous Driving
Mingzhe Guo, Yixiang Yang, Chuanrong Han +4
Effective environment modeling is the foundation for autonomous driving, underpinning tasks from perception to planning. However, current paradigms often inadequately consider the…
3D Part Assembly Generation with Instance Encoded Transformer
Rufeng Zhang, Tao Kong, Weihao Wang +2
It is desirable to enable robots capable of automatic assembly. Structural understanding of object parts plays a crucial role in this task yet remains relatively unexplored. In thi…
Self-Supervised Learning by Estimating Twin Class Distributions
Feng Wang, Tao Kong, Rufeng Zhang +2
We present TWIST, a simple and theoretically explainable self-supervised representation learning method by classifying large-scale unlabeled datasets in an end-to-end way. We emplo…
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…
Part-Guided Attention Learning for Vehicle Instance Retrieval
Xinyu Zhang, Rufeng Zhang, Jiewei Cao +3
Vehicle instance retrieval often requires one to recognize the fine-grained visual differences between vehicles. Besides the holistic appearance of vehicles which is easily affecte…