140 citations · 919 across the 60 of their papers we have counts for
11 papers · 1 filter
Embracing Single Stride 3D Object Detector with Sparse Transformer
Lue Fan, Ziqi Pang, Tianyuan Zhang +5
In LiDAR-based 3D object detection for autonomous driving, the ratio of the object size to input scene size is significantly smaller compared to 2D detection cases. Overlooking thi…
Immortal Tracker: Tracklet Never Dies
Qitai Wang, Yuntao Chen, Ziqi Pang +2
Previous online 3D Multi-Object Tracking(3DMOT) methods terminate a tracklet when it is not associated with new detections for a few frames. But if an object just goes dark, like b…
GAIA: A Transfer Learning System of Object Detection that Fits Your Needs
Xingyuan Bu, Junran Peng, Junjie Yan +2
Transfer learning with pre-training on large-scale datasets has played an increasingly significant role in computer vision and natural language processing recently. However, as the…
A Curriculum-style Self-training Approach for Source-Free Semantic Segmentation
Yuxi Wang, Jian Liang, Zhaoxiang Zhang
Source-free domain adaptation has developed rapidly in recent years, where the well-trained source model is adapted to the target domain instead of the source data, offering the po…
Image Inpainting by End-to-End Cascaded Refinement with Mask Awareness
Manyu Zhu, Dongliang He, Xin Li +5
Inpainting arbitrary missing regions is challenging because learning valid features for various masked regions is nontrivial. Though U-shaped encoder-decoder frameworks have been w…
Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy
Zikai Zhang, Bineng Zhong, Shengping Zhang +3
A practical long-term tracker typically contains three key properties, i.e. an efficient model design, an effective global re-detection strategy and a robust distractor awareness m…
RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features
Gang Zhang, Xin Lu, Jingru Tan +4
The two-stage methods for instance segmentation, e.g. Mask R-CNN, have achieved excellent performance recently. However, the segmented masks are still very coarse due to the downsa…
Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation
Chufeng Tang, Hang Chen, Xiao Li +3
Tremendous efforts have been made on instance segmentation but the mask quality is still not satisfactory. The boundaries of predicted instance masks are usually imprecise due to t…
Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression
Zigang Geng, Ke Sun, Bin Xiao +2
In this paper, we are interested in the bottom-up paradigm of estimating human poses from an image. We study the dense keypoint regression framework that is previously inferior to…
Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Tracking
Jiawei He, Zehao Huang, Naiyan Wang +1
Data association across frames is at the core of Multiple Object Tracking (MOT) task. This problem is usually solved by a traditional graph-based optimization or directly learned v…
RangeDet:In Defense of Range View for LiDAR-based 3D Object Detection
Lue Fan, Xuan Xiong, Feng Wang +2
In this paper, we propose an anchor-free single-stage LiDAR-based 3D object detector -- RangeDet. The most notable difference with previous works is that our method is purely based…