46 citations · 85 across the 7 of their papers we have counts for
10 papers
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…
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…
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…
Learning Implicit Temporal Alignment for Few-shot Video Classification
Songyang Zhang, Jiale Zhou, Xuming He
Few-shot video classification aims to learn new video categories with only a few labeled examples, alleviating the burden of costly annotation in real-world applications. However,…
Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation
Rongjie Li, Songyang Zhang, Bo Wan +1
Scene graph generation is an important visual understanding task with a broad range of vision applications. Despite recent tremendous progress, it remains challenging due to the in…
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…