10 citations · 28 across the 11 of their papers we have counts for
4 papers · 1 filter
MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models
Dohwan Ko, Joonmyung Choi, Hyeong Kyu Choi +3
Foundation models have shown outstanding performance and generalization capabilities across domains. Since most studies on foundation models mainly focus on the pretraining phase,…
Video-Text Representation Learning via Differentiable Weak Temporal Alignment
Dohwan Ko, Joonmyung Choi, Juyeon Ko +4
Learning generic joint representations for video and text by a supervised method requires a prohibitively substantial amount of manually annotated video datasets. As a practical al…
MSTR: Multi-Scale Transformer for End-to-End Human-Object Interaction Detection
Bumsoo Kim, Jonghwan Mun, Kyoung-Woon On +3
Human-Object Interaction (HOI) detection is the task of identifying a set of <human, object, interaction> triplets from an image. Recent work proposed transformer encoder-decoder a…
Winning the ICCV'2021 VALUE Challenge: Task-aware Ensemble and Transfer Learning with Visual Concepts
Minchul Shin, Jonghwan Mun, Kyoung-Woon On +3
The VALUE (Video-And-Language Understanding Evaluation) benchmark is newly introduced to evaluate and analyze multi-modal representation learning algorithms on three video-and-lang…