1 citations · 2 across the 7 of their papers we have counts for
7 papers
Activating Self-Attention for Multi-Scene Absolute Pose Regression
Miso Lee, Jihwan Kim, Jae-Pil Heo
Multi-scene absolute pose regression addresses the demand for fast and memory-efficient camera pose estimation across various real-world environments. Nowadays, transformer-based m…
Long-term Pre-training for Temporal Action Detection with Transformers
Jihwan Kim, Miso Lee, Jae-Pil Heo
Temporal action detection (TAD) is challenging, yet fundamental for real-world video applications. Recently, DETR-based models for TAD have been prevailing thanks to their unique b…
Boundary-Recovering Network for Temporal Action Detection
Jihwan Kim, Jaehyun Choi, Yerim Jeon +1
Temporal action detection (TAD) is challenging, yet fundamental for real-world video applications. Large temporal scale variation of actions is one of the most primary difficulties…
Prediction-Feedback DETR for Temporal Action Detection
Jihwan Kim, Miso Lee, Cheol-Ho Cho +2
Temporal Action Detection (TAD) is fundamental yet challenging for real-world video applications. Leveraging the unique benefits of transformers, various DETR-based approaches have…
Mutually-Aware Feature Learning for Few-Shot Object Counting
Yerim Jeon, Subeen Lee, Jihwan Kim +1
Few-shot object counting has garnered significant attention for its practicality as it aims to count target objects in a query image based on given exemplars without additional tra…
Self-Feedback DETR for Temporal Action Detection
Jihwan Kim, Miso Lee, Jae-Pil Heo
Temporal Action Detection (TAD) is challenging but fundamental for real-world video applications. Recently, DETR-based models have been devised for TAD but have not performed well…
Tailoring Self-Supervision for Supervised Learning
WonJun Moon, Ji-Hwan Kim, Jae-Pil Heo
Recently, it is shown that deploying a proper self-supervision is a prospective way to enhance the performance of supervised learning. Yet, the benefits of self-supervision are not…