9 citations · 28 across the 8 of their papers we have counts for
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cs.CV2022
Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene Segmentation
Liang Zeng, Attila Lengyel, Nergis Tömen +1
In this work, we leverage estimated depth to boost self-supervised contrastive learning for segmentation of urban scenes, where unlabeled videos are readily available for training…
cs.LG2022★ 2 cited
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification
Liang Zeng, Lanqing Li, Ziqi Gao +2
Graph contrastive learning (GCL) has attracted a surge of attention due to its superior performance for learning node/graph representations without labels. However, in practice, th…
cs.LG2022★ 6 cited
Spatio-Temporal meets Wavelet: Disentangled Traffic Flow Forecasting via Efficient Spectral Graph Attention Network
Yuchen Fang, Yanjun Qin, Haiyong Luo +4
Traffic forecasting is crucial for public safety and resource optimization, yet is very challenging due to three aspects: i) current existing works mostly exploit intricate tempora…