43 citations · 94 across the 10 of their papers we have counts for
10 papers
Diffusion-based Image Translation with Label Guidance for Domain Adaptive Semantic Segmentation
Duo Peng, Ping Hu, Qiuhong Ke +1
Translating images from a source domain to a target domain for learning target models is one of the most common strategies in domain adaptive semantic segmentation (DASS). However,…
DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition with Limited Annotations
Ping Hu, Ximeng Sun, Stan Sclaroff +1
Multi-label image recognition in the low-label regime is a task of great challenge and practical significance. Previous works have focused on learning the alignment between textual…
Token Boosting for Robust Self-Supervised Visual Transformer Pre-training
Tianjiao Li, Lin Geng Foo, Ping Hu +4
Learning with large-scale unlabeled data has become a powerful tool for pre-training Visual Transformers (VTs). However, prior works tend to overlook that, in real-world scenarios,…
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations
Ximeng Sun, Ping Hu, Kate Saenko
Solving multi-label recognition (MLR) for images in the low-label regime is a challenging task with many real-world applications. Recent work learns an alignment between textual an…
Learning to Detect Every Thing in an Open World
Kuniaki Saito, Ping Hu, Trevor Darrell +1
Many open-world applications require the detection of novel objects, yet state-of-the-art object detection and instance segmentation networks do not excel at this task. The key iss…
Conterfactual Generative Zero-Shot Semantic Segmentation
Feihong Shen, Jun Liu, Ping Hu
zero-shot learning is an essential part of computer vision. As a classical downstream task, zero-shot semantic segmentation has been studied because of its applicant value. One of…