Dahuin Jung
17 papers · 2019–2025 · 7 conferences · across top CS/AI conferences
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Conferences
ICML (4)
NIPS (4)
ICLR (3)
ECCV (2)
ICCV (2)
AAAI (1)
JMLR (1)
Top co-authors
Keywords
self-supervised learning
(2)
vision-language model
(2)
out-of-distribution detection
(2)
continual learning
(2)
vision language model
(2)
vision transformer
(2)
sample efficiency
(1)
transfer learning
(1)
image segmentation
(1)
imitation learning
(1)
image generation
(1)
uncertainty quantification
(1)
video frame interpolation
(1)
semantic segmentation
(1)
interpretable machine learning
(1)
multimodal learning
(1)
source-free domain adaptation
(1)
confidence calibration
(1)
channel attention
(1)
adversarial learning
(1)
Papers
Disentangled Motion Modeling for Video Frame Interpolation
AAAI 2025
Know "No" Better: A Data-Driven Approach for Enhancing Negation Awareness in CLIP
ICCV 2025
Sample-efficient Adversarial Imitation Learning
JMLR 2024
Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection
NIPS 2024
Efficient Diffusion-Driven Corruption Editor for Test-Time Adaptation
ECCV 2024
Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors
ICLR 2024
Improving Visual Prompt Tuning for Self-supervised Vision Transformers
ICML 2023
Generating Instance-level Prompts for Rehearsal-free Continual Learning
ICCV 2023
CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence
NIPS 2023
New Insights for the Stability-Plasticity Dilemma in Online Continual Learning
ICLR 2023
PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising
NIPS 2023
Probabilistic Concept Bottleneck Models
ICML 2023
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection
NIPS 2023
Stein Latent Optimization for Generative Adversarial Networks
ICLR 2022
Confidence Score for Source-Free Unsupervised Domain Adaptation
ICML 2022
iCaps: An Interpretable Classifier via Disentangled Capsule Networks
ECCV 2020
HexaGAN: Generative Adversarial Nets for Real World Classification
ICML 2019