6 citations · 11 across the 5 of their papers we have counts for
5 papers
Context Enhanced Transformer for Single Image Object Detection
Seungjun An, Seonghoon Park, Gyeongnyeon Kim +3
With the increasing importance of video data in real-world applications, there is a rising need for efficient object detection methods that utilize temporal information. While exis…
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Models
Gyeongnyeon Kim, Wooseok Jang, Gyuseong Lee +3
Generative models have recently undergone significant advancement due to the diffusion models. The success of these models can be often attributed to their use of guidance techniqu…
MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth Estimation
Jongbeom Baek, Gyeongnyeon Kim, Seonghoon Park +3
We propose MaskingDepth, a novel semi-supervised learning framework for monocular depth estimation to mitigate the reliance on large ground-truth depth quantities. MaskingDepth is…
InstaFormer: Instance-Aware Image-to-Image Translation with Transformer
Soohyun Kim, Jongbeom Baek, Jihye Park +2
We present a novel Transformer-based network architecture for instance-aware image-to-image translation, dubbed InstaFormer, to effectively integrate global- and instance-level inf…
Semi-Supervised Learning with Mutual Distillation for Monocular Depth Estimation
Jongbeom Baek, Gyeongnyeon Kim, Seungryong Kim
We propose a semi-supervised learning framework for monocular depth estimation. Compared to existing semi-supervised learning methods, which inherit limitations of both sparse supe…