most citedCross-aware Early Fusion with Stage-divided Vision and Language Transformer Encoders for Referring Image Segmentation

38 citations · 38 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

SparSTAR: Sparse Attention for SpaceTime AutoRegressive Video Synthesis

Jongbeom Lee, Hyunwoo Yu, Jincheol Yang +2

InfinityStar extends visual autoregressive generation to video through a sequence of image and clip pyramids. Its changing scale and cross-clip context, however, leave late-scale a…

cs.CV2026

VIPA: Visual Informative Part Attention for Referring Image Segmentation

Yubin Cho, Hyunwoo Yu, Kyeongbo Kong +3

Referring Image Segmentation (RIS) aims to segment a target object described by a natural language expression. Existing methods have evolved by leveraging the vision information in…

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.CV202438 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…