49 citations · 184 across the 40 of their papers we have counts for
7 papers · 1 filter
Knowing Where to Focus: Event-aware Transformer for Video Grounding
Jinhyun Jang, Jungin Park, Jin Kim +2
Recent DETR-based video grounding models have made the model directly predict moment timestamps without any hand-crafted components, such as a pre-defined proposal or non-maximum s…
Semantic-aware Network for Aerial-to-Ground Image Synthesis
Jinhyun Jang, Taeyong Song, Kwanghoon Sohn
Aerial-to-ground image synthesis is an emerging and challenging problem that aims to synthesize a ground image from an aerial image. Due to the highly different layout and object r…
Hierarchical Visual Primitive Experts for Compositional Zero-Shot Learning
Hanjae Kim, Jiyoung Lee, Seongheon Park +1
Compositional zero-shot learning (CZSL) aims to recognize unseen compositions with prior knowledge of known primitives (attribute and object). Previous works for CZSL often suffer…
PartMix: Regularization Strategy to Learn Part Discovery for Visible-Infrared Person Re-identification
Minsu Kim, Seungryong Kim, JungIn Park +2
Modern data augmentation using a mixture-based technique can regularize the models from overfitting to the training data in various computer vision applications, but a proper data…
Probabilistic Prompt Learning for Dense Prediction
Hyeongjun Kwon, Taeyong Song, Somi Jeong +3
Recent progress in deterministic prompt learning has become a promising alternative to various downstream vision tasks, enabling models to learn powerful visual representations wit…
Dual-path Adaptation from Image to Video Transformers
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
In this paper, we efficiently transfer the surpassing representation power of the vision foundation models, such as ViT and Swin, for video understanding with only a few trainable…
TemporalMaxer: Maximize Temporal Context with only Max Pooling for Temporal Action Localization
Tuan N. Tang, Kwonyoung Kim, Kwanghoon Sohn
Temporal Action Localization (TAL) is a challenging task in video understanding that aims to identify and localize actions within a video sequence. Recent studies have emphasized t…