activity
20212026
most citedGrounded Situation Recognition with Transformers

7 citations · 17 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

SceneAligner: 3D-Grounded Floorplan Localization in the Wild

Junhyeong Cho, Ruojin Cai, Hadar Averbuch-Elor

Many public buildings provide floorplans with a "you are here" indicator to help visitors orient themselves. Floorplan localization seeks to computationally replicate this capabili…

cs.CV2024

Robust 3D Shape Reconstruction in Zero-Shot from a Single Image in the Wild

Junhyeong Cho, Kim Youwang, Hunmin Yang +1

Recent monocular 3D shape reconstruction methods have shown promising zero-shot results on object-segmented images without any occlusions. However, their effectiveness is significa…

cs.CV2023★ 5 cited

PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization

Junhyeong Cho, Gilhyun Nam, Sungyeon Kim +2

In a joint vision-language space, a text feature (e.g., from "a photo of a dog") could effectively represent its relevant image features (e.g., from dog photos). Also, a recent stu…

cs.CV2022★ 3 cited

Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformers

Junhyeong Cho, Kim Youwang, Tae-Hyun Oh

Transformer encoder architectures have recently achieved state-of-the-art results on monocular 3D human mesh reconstruction, but they require a substantial number of parameters and…

cs.CV2022★ 2 cited

Collaborative Transformers for Grounded Situation Recognition

Junhyeong Cho, Youngseok Yoon, Suha Kwak

Grounded situation recognition is the task of predicting the main activity, entities playing certain roles within the activity, and bounding-box groundings of the entities in the g…

cs.CV2021★ 7 cited

Grounded Situation Recognition with Transformers

Junhyeong Cho, Youngseok Yoon, Hyeonjun Lee +1

Grounded Situation Recognition (GSR) is the task that not only classifies a salient action (verb), but also predicts entities (nouns) associated with semantic roles and their locat…