Search Results for author: Yanwei Li

Found 14 papers, 9 papers with code

Focal Sparse Convolutional Networks for 3D Object Detection

2 code implementations26 Apr 2022 Yukang Chen, Yanwei Li, Xiangyu Zhang, Jian Sun, Jiaya Jia

In this paper, we introduce two new modules to enhance the capability of Sparse CNNs, both are based on making feature sparsity learnable with position-wise importance prediction.

3D Object Detection

Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision

1 code implementation17 Aug 2021 Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, Yukang Chen, Lu Qi, LiWei Wang, Zeming Li, Jian Sun, Jiaya Jia

In particular, Panoptic FCN encodes each object instance or stuff category with the proposed kernel generator and produces the prediction by convolving the high-resolution feature directly.

Panoptic Segmentation Weakly-supervised panoptic segmentation

Fine-Grained Dynamic Head for Object Detection

1 code implementation NeurIPS 2020 Lin Song, Yanwei Li, Zhengkai Jiang, Zeming Li, Hongbin Sun, Jian Sun, Nanning Zheng

To this end, we propose a fine-grained dynamic head to conditionally select a pixel-level combination of FPN features from different scales for each instance, which further releases the ability of multi-scale feature representation.

Object Detection

Fully Convolutional Networks for Panoptic Segmentation

5 code implementations CVPR 2021 Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, LiWei Wang, Zeming Li, Jian Sun, Jiaya Jia

In this paper, we present a conceptually simple, strong, and efficient framework for panoptic segmentation, called Panoptic FCN.

 Ranked #1 on Panoptic Segmentation on Cityscapes val (PQst metric)

Panoptic Segmentation

Dynamic Scale Training for Object Detection

4 code implementations26 Apr 2020 Yukang Chen, Peizhen Zhang, Zeming Li, Yanwei Li, Xiangyu Zhang, Lu Qi, Jian Sun, Jiaya Jia

We propose a Dynamic Scale Training paradigm (abbreviated as DST) to mitigate scale variation challenge in object detection.

Instance Segmentation Object Detection +1

Learning Dynamic Routing for Semantic Segmentation

no code implementations CVPR 2020 Yanwei Li, Lin Song, Yukang Chen, Zeming Li, Xiangyu Zhang, Xingang Wang, Jian Sun

To demonstrate the superiority of the dynamic property, we compare with several static architectures, which can be modeled as special cases in the routing space.

Semantic Segmentation

FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks

no code implementations15 Aug 2019 Jiabin Zhang, Zheng Zhu, Wei Zou, Peng Li, Yanwei Li, Hu Su, Guan Huang

Given the results of MTN, we adopt an occlusion-aware Re-ID feature strategy in the pose tracking module, where pose information is utilized to infer the occlusion state to make better use of Re-ID feature.

Human Detection Multi-Person Pose Estimation +3

State-aware Re-identification Feature for Multi-target Multi-camera Tracking

no code implementations4 Jun 2019 Peng Li, Jiabin Zhang, Zheng Zhu, Yanwei Li, Lu Jiang, Guan Huang

Multi-target Multi-camera Tracking (MTMCT) aims to extract the trajectories from videos captured by a set of cameras.

Identity-Enhanced Network for Facial Expression Recognition

no code implementations11 Dec 2018 Yanwei Li, Xingang Wang, Shilei Zhang, Lingxi Xie, Wenqi Wu, Hongyuan Yu, Zheng Zhu

Facial expression recognition is a challenging task, arguably because of large intra-class variations and high inter-class similarities.

Facial Expression Recognition Multi-Task Learning

Attention-guided Unified Network for Panoptic Segmentation

no code implementations CVPR 2019 Yanwei Li, Xinze Chen, Zheng Zhu, Lingxi Xie, Guan Huang, Dalong Du, Xingang Wang

This paper studies panoptic segmentation, a recently proposed task which segments foreground (FG) objects at the instance level as well as background (BG) contents at the semantic level.

Panoptic Segmentation

Cannot find the paper you are looking for? You can Submit a new open access paper.