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20172022
most citedYOLOX: Exceeding YOLO Series in 2021

3k citations · 3.5k across the 20 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.CV20213k cited

YOLOX: Exceeding YOLO Series in 2021

Zheng Ge, Songtao Liu, Feng Wang +2

In this report, we present some experienced improvements to YOLO series, forming a new high-performance detector -- YOLOX. We switch the YOLO detector to an anchor-free manner and…

cs.CV20217 cited

Workshop on Autonomous Driving at CVPR 2021: Technical Report for Streaming Perception Challenge

Songyang Zhang, Lin Song, Songtao Liu +4

In this report, we introduce our real-time 2D object detection system for the realistic autonomous driving scenario. Our detector is built on a newly designed YOLO model, called YO…

cs.CV202121 cited

Generalized Few-Shot Object Detection without Forgetting

Zhibo Fan, Yuchen Ma, Zeming Li +1

Recently few-shot object detection is widely adopted to deal with data-limited situations. While most previous works merely focus on the performance on few-shot categories, we clai…

cs.CV20213 cited

IQDet: Instance-wise Quality Distribution Sampling for Object Detection

Yuchen Ma, Songtao Liu, Zeming Li +1

We propose a dense object detector with an instance-wise sampling strategy, named IQDet. Instead of using human prior sampling strategies, we first extract the regional feature of…

cs.CV202124 cited

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

Songyang Zhang, Zeming Li, Shipeng Yan +2

Despite the recent success of deep neural networks, it remains challenging to effectively model the long-tail class distribution in visual recognition tasks. To address this proble…

cs.CV20217 cited

OTA: Optimal Transport Assignment for Object Detection

Zheng Ge, Songtao Liu, Zeming Li +2

Recent advances in label assignment in object detection mainly seek to independently define positive/negative training samples for each ground-truth (gt) object. In this paper, we…