78 citations · 107 across the 9 of their papers we have counts for
9 papers
Anomaly-Aware Semantic Segmentation via Style-Aligned OoD Augmentation
Dan Zhang, Kaspar Sakmann, William Beluch +2
Within the context of autonomous driving, encountering unknown objects becomes inevitable during deployment in the open world. Therefore, it is crucial to equip standard semantic s…
Contrastive Representation Disentanglement for Clustering
Fei Ding, Dan Zhang, Yin Yang +2
Clustering continues to be a significant and challenging task. Recent studies have demonstrated impressive results by applying clustering to feature representations acquired throug…
Divide & Bind Your Attention for Improved Generative Semantic Nursing
Yumeng Li, Margret Keuper, Dan Zhang +1
Emerging large-scale text-to-image generative models, e.g., Stable Diffusion (SD), have exhibited overwhelming results with high fidelity. Despite the magnificent progress, current…
Multi-level Distillation of Semantic Knowledge for Pre-training Multilingual Language Model
Mingqi Li, Fei Ding, Dan Zhang +3
Pre-trained multilingual language models play an important role in cross-lingual natural language understanding tasks. However, existing methods did not focus on learning the seman…
TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross-Task Consistency
Dan Zhang, Rui Zheng, Luosang Gadeng +1
This paper addresses the task of semantic segmentation in computer vision, aiming to achieve precise pixel-wise classification. We investigate the joint training of models for sema…
Semantics-aware Dataset Discovery from Data Lakes with Contextualized Column-based Representation Learning
Grace Fan, Jin Wang, Yuliang Li +2
Dataset discovery from data lakes is essential in many real application scenarios. In this paper, we propose Starmie, an end-to-end framework for dataset discovery from data lakes…
Panoptic-PHNet: Towards Real-Time and High-Precision LiDAR Panoptic Segmentation via Clustering Pseudo Heatmap
Jinke Li, Xiao He, Yang Wen +3
As a rising task, panoptic segmentation is faced with challenges in both semantic segmentation and instance segmentation. However, in terms of speed and accuracy, existing LiDAR me…
Annotating Columns with Pre-trained Language Models
Yoshihiko Suhara, Jinfeng Li, Yuliang Li +4
Inferring meta information about tables, such as column headers or relationships between columns, is an active research topic in data management as we find many tables are missing…
Sato: Contextual Semantic Type Detection in Tables
Dan Zhang, Yoshihiko Suhara, Jinfeng Li +3
Detecting the semantic types of data columns in relational tables is important for various data preparation and information retrieval tasks such as data cleaning, schema matching,…