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Shan Yang

4 papers hereh-index 3825 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.LG1
same name
  • Shan Yang — 14 papers, h 25
  • Shan Yang — 8 papers, h 11
  • Shan Yang — 6 papers, h 3
  • Shan Yang — 6 papers, h 3
  • Shan Yang — 6 papers, h 2
  • Shan Yang — 6 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212023
most citedAttention Bottlenecks for Multimodal Fusion

268 citations · 288 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

ICAR: Image-based Complementary Auto Reasoning

Xijun Wang, Anqi Liang, Junbang Liang +3

Scene-aware Complementary Item Retrieval (CIR) is a challenging task which requires to generate a set of compatible items across domains. Due to the subjectivity, it is difficult t…

cs.LG2022★ 1 cited

Investigation of Factorized Optical Flows as Mid-Level Representations

Hsuan-Kung Yang, Tsu-Ching Hsiao, Ting-Hsuan Liao +7

In this paper, we introduce a new concept of incorporating factorized flow maps as mid-level representations, for bridging the perception and the control modules in modular learnin…

cs.CV2022★ 19 cited

Deep Graph Learning for Spatially-Varying Indoor Lighting Prediction

Jiayang Bai, Jie Guo, Chenchen Wan +6

Lighting prediction from a single image is becoming increasingly important in many vision and augmented reality (AR) applications in which shading and shadow consistency between vi…

cs.CV2021★ 268 cited

Attention Bottlenecks for Multimodal Fusion

Arsha Nagrani, Shan Yang, Anurag Arnab +3

Humans perceive the world by concurrently processing and fusing high-dimensional inputs from multiple modalities such as vision and audio. Machine perception models, in stark contr…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.