Myungsub Choi
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    • 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.
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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
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 →

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