4 papers
A-SelecT: Automatic Timestep Selection for Diffusion Transformer Representation Learning
Changyu Liu, James Chenhao Liang, Wenhao Yang +6
Diffusion models have significantly reshaped the field of generative artificial intelligence and are now increasingly explored for their capacity in discriminative representation l…
Boosting Active Learning with Knowledge Transfer
Tianyang Wang, Xi Xiao, Gaofei Chen +3
Uncertainty estimation is at the core of Active Learning (AL). Most existing methods resort to complex auxiliary models and advanced training fashions to estimate uncertainty for u…
TASAM: Terrain-and-Aware Segment Anything Model for Temporal-Scale Remote Sensing Segmentation
Tianyang Wang, Xi Xiao, Gaofei Chen +4
Segment Anything Model (SAM) has demonstrated impressive zero-shot segmentation capabilities across natural image domains, but it struggles to generalize to the unique challenges o…
Deep Active Learning with Manifold-preserving Trajectory Sampling
Yingrui Ji, Vijaya Sindhoori Kaza, Nishanth Artham +1
Active learning (AL) is for optimizing the selection of unlabeled data for annotation (labeling), aiming to enhance model performance while minimizing labeling effort. The key ques…