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20162022
most citedLatentGNN: Learning Efficient Non-local Relations for Visual Recognition

46 citations · 115 across the 16 of their papers we have counts for

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19 papers · 1 filter

cs.CV20222 cited

Generative Negative Text Replay for Continual Vision-Language Pretraining

Shipeng Yan, Lanqing Hong, Hang Xu +4

Vision-language pre-training (VLP) has attracted increasing attention recently. With a large amount of image-text pairs, VLP models trained with contrastive loss have achieved impr…

cs.CV2022

Budget-aware Few-shot Learning via Graph Convolutional Network

Shipeng Yan, Songyang Zhang, Xuming He

This paper tackles the problem of few-shot learning, which aims to learn new visual concepts from a few examples. A common problem setting in few-shot classification assumes random…

cs.CV2021

Single Image 3D Object Estimation with Primitive Graph Networks

Qian He, Desen Zhou, Bo Wan +1

Reconstructing 3D object from a single image (RGB or depth) is a fundamental problem in visual scene understanding and yet remains challenging due to its ill-posed nature and compl…

cs.CV20218 cited

Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition

Tailin Chen, Desen Zhou, Jian Wang +4

The task of skeleton-based action recognition remains a core challenge in human-centred scene understanding due to the multiple granularities and large variation in human motion. E…

cs.CV20211 cited

An EM Framework for Online Incremental Learning of Semantic Segmentation

Shipeng Yan, Jiale Zhou, Jiangwei Xie +2

Incremental learning of semantic segmentation has emerged as a promising strategy for visual scene interpretation in the open- world setting. However, it remains challenging to acq…

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…