◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

S. Cheung

4 papers hereh-index 6197 citations24 works total

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

author position
  • middle author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG1
  • eess.IV1
same name
  • S. Cheung — 25 papers, h 5
  • S. Cheung — 17 papers, h 49
  • S. Cheung — 5 papers, h 4
  • S. Cheung — 3 papers, h 2
  • S. Cheung — 2 papers, h 73
  • S. Cheung — 1 paper, h 4

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

collaborators

4 papers

cs.CV2026

Boundary-Centric Clip-Budgeted Active Learning for Temporal Action Segmentation

Halil Ismail Helvaci, Sen-ching Samson Cheung

Temporal action segmentation (TAS) in untrimmed videos requires dense temporal supervision. However, most of the annotation cost is spent identifying action transitions where segme…

eess.IV2026

Learning Class Difficulty via Dynamic Focal Attention for Histopathology Segmentation

Lakmali Nadeesha Kumari, Lakmali Nadeesha Kumari Rathukohe Mudiyanselage, Sen-Ching Samson Cheung

Frequency-based loss reweighting, the standard remedy for imbalanced histopathology segmentation, implicitly assumes that rare classes are difficult. Yet difficulty also arises fro…

cs.CV2026

MMTA: Multi Membership Temporal Attention for Fine-Grained Stroke Rehabilitation Assessment

Halil Ismail Helvaci, Justin Huber, Jihye Bae +1

To empower the iterative assessments involved during a person's rehabilitation, automated assessment of a person's abilities during daily activities requires temporally precise seg…

cs.LG2026

Empowering Source-Free Domain Adaptation via MLLM-Guided Reliability-Based Curriculum Learning

Dongjie Chen, Kartik Patwari, Zhengfeng Lai +3

Existing SFDA methods struggle to fully use pre-trained knowledge and often rely on a single model's predictions or handcrafted prompts, limiting robustness under domain shift. Mul…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.