Search Results for author:
Found 6 papers, 4 papers with code
Overcoming Overconfidence for Active Learning
Active learning is a prominent approach for addressing this issue, where valuable data for labeling is selected through a model and utilized to iteratively adjust the model.
VVS: Video-to-Video Retrieval with Irrelevant Frame Suppression
In content-based video retrieval (CBVR), dealing with large-scale collections, efficiency is as important as accuracy; thus, several video-level feature-based studies have actively been conducted.
Ranked #12 on
Video Retrieval
on FIVR-200K
TransDSSL: Transformer based Depth Estimation via Self-Supervised Learning
Recently, transformers have been widely adopted for various computer vision tasks and show promising results due to their ability to encode long-range spatial dependencies in an image effectively.
Ranked #3 on
Monocular Depth Estimation
on DDAD
Exploring the Temporal Cues to Enhance Video Retrieval on Standardized CDVA
As the demand for large-scale video analysis increases, video retrieval research is also becoming more active.
Ranked #8 on
Video Retrieval
on FIVR-200K
MLPD: Multi-Label Pedestrian Detector in Multispectral Domain
In this letter, we tackle multispectral pedestrian detection, where all input data are not paired.
Multispectral Pedestrian Detection: Benchmark Dataset and Baseline
With this dataset, we introduce multispectral ACF, which is an extension of aggregated channel features (ACF) to simultaneously handle color-thermal image pairs.
