b'Zeming Li'

research

∙ 11/19/2022

MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception

This paper proposes an efficient multi-camera to Bird's-Eye-View (BEV) v...

5 Hongyu Zhou, et al. ∙

research

∙ 08/22/2022

STS: Surround-view Temporal Stereo for Multi-view 3D Detection

Learning accurate depth is essential to multi-view 3D object detection. ...

0 Zengran Wang, et al. ∙

research

∙ 08/19/2022

PersDet: Monocular 3D Detection in Perspective Bird's-Eye-View

Currently, detecting 3D objects in Bird's-Eye-View (BEV) is superior to ...

0 Hongyu Zhou, et al. ∙

research

∙ 07/13/2022

DSPNet: Towards Slimmable Pretrained Networks based on Discriminative Self-supervised Learning

Self-supervised learning (SSL) has achieved promising downstream perform...

0 Shaoru Wang, et al. ∙

research

∙ 07/06/2022

Dense Teacher: Dense Pseudo-Labels for Semi-supervised Object Detection

To date, the most powerful semi-supervised object detectors (SS-OD) are ...

0 Hongyu Zhou, et al. ∙

research

∙ 06/01/2022

Unifying Voxel-based Representation with Transformer for 3D Object Detection

In this work, we present a unified framework for multi-modality 3D objec...

0 Yanwei Li, et al. ∙

research

∙ 05/31/2022

Voxel Field Fusion for 3D Object Detection

In this work, we present a conceptually simple yet effective framework f...

0 Yanwei Li, et al. ∙

research

∙ 05/28/2022

A Closer Look at Self-supervised Lightweight Vision Transformers

Self-supervised learning on large-scale Vision Transformers (ViTs) as pr...

0 Shaoru Wang, et al. ∙

research

∙ 03/23/2022

Real-time Object Detection for Streaming Perception

Autonomous driving requires the model to perceive the environment and (r...

0 Jinrong Yang, et al. ∙

research

∙ 03/22/2022

Rebalanced Siamese Contrastive Mining for Long-Tailed Recognition

Deep neural networks perform poorly on heavily class-imbalanced datasets...

0 Zhisheng Zhong, et al. ∙

research

∙ 08/17/2021

Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision

In this paper, we present a conceptually simple, strong, and efficient f...

0 Yanwei Li, et al. ∙

research

∙ 07/18/2021

YOLOX: Exceeding YOLO Series in 2021

In this report, we present some experienced improvements to YOLO series,...

0 Zheng Ge, et al. ∙

research

∙ 05/20/2021

Generalized Few-Shot Object Detection without Forgetting

Recently few-shot object detection is widely adopted to deal with data-l...

17 Zhibo Fan, et al. ∙

research

∙ 04/14/2021

IQDet: Instance-wise Quality Distribution Sampling for Object Detection

We propose a dense object detector with an instance-wise sampling strate...

0 Yuchen Ma, et al. ∙

research

∙ 03/30/2021

Distribution Alignment: A Unified Framework for Long-tail Visual Recognition

Despite the recent success of deep neural networks, it remains challengi...

20 Songyang Zhang, et al. ∙

research

∙ 03/26/2021

OTA: Optimal Transport Assignment for Object Detection

Recent advances in label assignment in object detection mainly seek to i...

0 Zheng Ge, et al. ∙

research

∙ 01/19/2021

Momentum^2 Teacher: Momentum Teacher with Momentum Statistics for Self-Supervised Learning

In this paper, we present a novel approach, Momentum^2 Teacher, for stud...

0 Zeming Li, et al. ∙

research

∙ 12/07/2020

End-to-End Object Detection with Fully Convolutional Network

Mainstream object detectors based on the fully convolutional network has...

0 Jianfeng Wang, et al. ∙

research

∙ 12/07/2020

Fine-Grained Dynamic Head for Object Detection

The Feature Pyramid Network (FPN) presents a remarkable approach to alle...

0 Lin Song, et al. ∙

research

∙ 12/07/2020

Rethinking Learnable Tree Filter for Generic Feature Transform

The Learnable Tree Filter presents a remarkable approach to model struct...

0 Lin Song, et al. ∙

research

∙ 12/01/2020

Fully Convolutional Networks for Panoptic Segmentation

In this paper, we present a conceptually simple, strong, and efficient f...

0 Yanwei Li, et al. ∙

research

∙ 11/27/2020

Self-EMD: Self-Supervised Object Detection without ImageNet

In this paper, we propose a novel self-supervised representation learnin...

0 Songtao Liu, et al. ∙

research

∙ 10/06/2020

Joint COCO and Mapillary Workshop at ICCV 2019: COCO Instance Segmentation Challenge Track

In this report, we present our object detection/instance segmentation sy...

0 Zeming Li, et al. ∙

research

∙ 10/05/2020

EqCo: Equivalent Rules for Self-supervised Contrastive Learning

In this paper, we propose a method, named EqCo (Equivalent Rules for Con...

3 Benjin Zhu, et al. ∙

research

∙ 07/21/2020

BorderDet: Border Feature for Dense Object Detection

Dense object detectors rely on the sliding-window paradigm that predicts...

0 Han Qiu, et al. ∙

research

∙ 07/07/2020

AutoAssign: Differentiable Label Assignment for Dense Object Detection

In this paper, we propose an anchor-free object detector with a fully di...

2 Benjin Zhu, et al. ∙

research

∙ 04/26/2020

Stitcher: Feedback-driven Data Provider for Object Detection

Object detectors commonly vary quality according to scales, where the pe...

3 Yukang Chen, et al. ∙

research

∙ 03/23/2020

Learning Dynamic Routing for Semantic Segmentation

Recently, numerous handcrafted and searched networks have been applied f...

4 Yanwei Li, et al. ∙

research

∙ 09/27/2019

Learnable Tree Filter for Structure-preserving Feature Transform

Learning discriminative global features plays a vital role in semantic s...

0 Lin Song, et al. ∙

research

∙ 08/26/2019

Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection

This report presents our method which wins the nuScenes3D Detection Chal...

5 Benjin Zhu, et al. ∙

research

∙ 03/28/2019

ThunderNet: Towards Real-time Generic Object Detection

Real-time generic object detection on mobile platforms is a crucial but ...

22 Zheng Qin, et al. ∙

research

∙ 04/17/2018

DetNet: A Backbone network for Object Detection

Recent CNN based object detectors, no matter one-stage methods like YOLO...

0 Zeming Li, et al. ∙

research

∙ 11/20/2017

Light-Head R-CNN: In Defense of Two-Stage Object Detector

In this paper, we first investigate why typical two-stage methods are no...

0 Zeming Li, et al. ∙

research

∙ 11/20/2017

MegDet: A Large Mini-Batch Object Detector

The improvements in recent CNN-based object detection works, from R-CNN ...

0 Chao Peng, et al. ∙

Zeming Li

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