Facial affective behavior analysis with instruction tuning

Y Li, A Dao, W Bao, Z Tan, T Chen, H Liu… - European Conference on …, 2024 - Springer
Facial affective behavior analysis (FABA) is crucial for understanding human mental states
from images. However, traditional approaches primarily deploy models to discriminate …

Gradorth: A simple yet efficient out-of-distribution detection with orthogonal projection of gradients

S Behpour, TL Doan, X Li, W He… - Advances in Neural …, 2023 - proceedings.neurips.cc
Detecting out-of-distribution (OOD) data is crucial for ensuring the safe deployment of
machine learning models in real-world applications. However, existing OOD detection …

Hyp-ow: Exploiting hierarchical structure learning with hyperbolic distance enhances open world object detection

T Doan, X Li, S Behpour, W He, L Gou… - Proceedings of the AAAI …, 2024 - ojs.aaai.org
Open World Object Detection (OWOD) is a challenging and realistic task that extends
beyond the scope of standard Object Detection task. It involves detecting both known and …

[HTML][HTML] Unsupervised selective labeling for semi-supervised industrial defect detection

J Ge, Q Qin, S Song, J Jiang, Z Shen - Journal of King Saud University …, 2024 - Elsevier
In industrial detection scenarios, achieving high accuracy typically relies on extensive
labeled datasets, which are costly and time-consuming. This has motivated a shift towards …

Object-Focused Data Selection for Dense Prediction Tasks

N Popp, D Zhang, JH Metzen, M Hein… - ar** Contrastive Pre-training for Data Efficiency
Y Guo, M Kankanhalli - arxiv preprint arxiv:2411.09126, 2024 - arxiv.org
While contrastive pre-training is widely employed, its data efficiency problem has remained
relatively under-explored thus far. Existing methods often rely on static coreset selection …