Myungsub Choi
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  • Talks
    • AI 에이전트의 런타임 신뢰성: 검증, 방어, 예측
    • As AI Gets Smarter, How Far Can Enterprises Delegate?
    • AI의 빈틈을 메우는 스타트업: 양질의 데이터·검증·금융 규제·거버넌스로 완성되는 신뢰
    • From Focusing Lenses to Focusing Risks: An Engineer's Journey into Agentic AI Safety
    • Cracking the Enterprise Code: How GenAI Startups Can Win Enterprise Deals
    • 신뢰할 수 있는 AI는 어떻게 만들어지는가 — Mission-Critical 환경의 RAG, Judge, 그리고 Agent 통제
    • Tynapse Startup Pitch at the 2026 AWS AI Pitch Competition
  • Publications
    • Beyond the Verdict: Evidence-Aligned Evaluation of Visual Prompt-Injection Guardrails
    • Risk Is Not Review Value: Wrong-Answer Exposure Under Bounded Review Budgets
    • Cross-Agent Campaign Attribution: Linking Asynchronous Attacks Across LLM Agents
    • Stable Autofocus with Focal Consistency Loss
    • Exploring Positional Characteristics of Dual-Pixel Data for Camera Autofocus
    • Learning to Learn Task-Adaptive Hyperparameters for Few-Shot Learning
    • Referring Object Manipulation of Natural Images with Conditional Classifier-Free Guidance
    • Visual Tracking by Adaptive Continual Meta-Learning
    • DynaVSR: Dynamic Adaptive Blind Video Super-Resolution
    • Motion-Aware Dynamic Architecture for Efficient Frame Interpolation
    • Searching for Controllable Image Restoration Networks
    • Test-Time Adaptation for Video Frame Interpolation via Meta-Learning
    • Channel Attention Is All You Need for Video Frame Interpolation
    • Meta-Learning with Adaptive Hyperparameters
    • Scene-Adaptive Video Frame Interpolation via Meta-Learning
    • AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results
    • Task-Aware Image Downscaling
  • Blog
    • 📄 A paper on evaluating visual prompt-injection guardrails is accepted in the BEAM 2 workshop at ECCV 2026 as an Oral presentation
    • 📄 A paper on review-budget-aware LLM evaluation is accepted in the SeT-LLM workshop at KDD 2026
    • 📄 A paper on cross-agent attack attribution is accepted in the AIWILD workshop at ICML 2026
    • 📄 A paper on stabilizing autofocus is accepted in WACV 2025 as an Oral presentation
    • 📄 A paper on autofocus is accepted in ICCV 2023.
  • Experience
  • Projects
  • Projects
    • Meta-VFI
    • CAIN
    • awesome-rnn

Channel Attention Is All You Need for Video Frame Interpolation

Jan 1, 2020·
Myungsub Choi
,
Heewon Kim
,
Bohyung Han
,
Ning Xu
,
Kyoung Mu Lee
· 0 min read
PDF DOI Code Project
Type
Conference paper
Publication
AAAI Conference on Artificial Intelligence (AAAI)
Last updated on Jan 1, 2020
← Test-Time Adaptation for Video Frame Interpolation via Meta-Learning Jan 1, 2021
Meta-Learning with Adaptive Hyperparameters Jan 1, 2020 →

© 2026 Myungsub Choi. This work is licensed under CC BY NC ND 4.0

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