2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CV2023★ 2 cited
USD: Unknown Sensitive Detector Empowered by Decoupled Objectness and Segment Anything Model
Yulin He, Wei Chen, Yusong Tan +1
Open World Object Detection (OWOD) is a novel and challenging computer vision task that enables object detection with the ability to detect unknown objects. Existing methods typica…
cs.CV2023
LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge Integration
Siqi Wang, Bryan A. Plummer
Learning with noisy labels (LNL) aims to train a high-performing model using a noisy dataset. We observe that noise for a given class often comes from a limited set of categories,…
cs.LG2023
Cross-modal Contrastive Learning for Multimodal Fake News Detection
Longzheng Wang, Chuang Zhang, Hongbo Xu +3
Automatic detection of multimodal fake news has gained a widespread attention recently. Many existing approaches seek to fuse unimodal features to produce multimodal news represent…