38 citations · 38 across the 4 of their papers we have counts for
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cs.CV2024
MetaSeg: MetaFormer-based Global Contexts-aware Network for Efficient Semantic Segmentation
Beoungwoo Kang, Seunghun Moon, Yubin Cho +2
Beyond the Transformer, it is important to explore how to exploit the capacity of the MetaFormer, an architecture that is fundamental to the performance improvements of the Transfo…
cs.CV2024★ 38 cited
Cross-aware Early Fusion with Stage-divided Vision and Language Transformer Encoders for Referring Image Segmentation
Yubin Cho, Hyunwoo Yu, Suk-ju Kang
Referring segmentation aims to segment a target object related to a natural language expression. Key challenges of this task are understanding the meaning of complex and ambiguous…
cs.CV2024
Embedding-Free Transformer with Inference Spatial Reduction for Efficient Semantic Segmentation
Hyunwoo Yu, Yubin Cho, Beoungwoo Kang +3
We present an Encoder-Decoder Attention Transformer, EDAFormer, which consists of the Embedding-Free Transformer (EFT) encoder and the all-attention decoder leveraging our Embeddin…