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20172025
most citedDecision Transformer: Reinforcement Learning via Sequence Modeling

465 citations · 839 across the 30 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

Improving Motion in Image-to-Video Models via Adaptive Low-Pass Guidance

June Suk Choi, Kyungmin Lee, Sihyun Yu +3

Recent text-to-video (T2V) models have demonstrated strong capabilities in producing high-quality, dynamic videos. To improve the visual controllability, recent works have consider…

cs.CV2023★ 25 cited

StyleDrop: Text-to-Image Generation in Any Style

Kihyuk Sohn, Nataniel Ruiz, Kimin Lee +11

Pre-trained large text-to-image models synthesize impressive images with an appropriate use of text prompts. However, ambiguities inherent in natural language and out-of-distributi…

cs.CV2022★ 1 cited

HARP: Autoregressive Latent Video Prediction with High-Fidelity Image Generator

Younggyo Seo, Kimin Lee, Fangchen Liu +2

Video prediction is an important yet challenging problem; burdened with the tasks of generating future frames and learning environment dynamics. Recently, autoregressive latent vid…

cs.CV2019

Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild

Kibok Lee, Kimin Lee, Jinwoo Shin +1

Lifelong learning with deep neural networks is well-known to suffer from catastrophic forgetting: the performance on previous tasks drastically degrades when learning a new task. T…

cs.CV2018

Hierarchical Novelty Detection for Visual Object Recognition

Kibok Lee, Kimin Lee, Kyle Min +3

Deep neural networks have achieved impressive success in large-scale visual object recognition tasks with a predefined set of classes. However, recognizing objects of novel classes…