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Xiaokang Liu

7 accepted papers

2026

RSOD: Reliability-Guided Sonar Image Object Detection with Extremely Limited Labels

AAAI 2026technical

Object detection in sonar images is a key technology in underwater detection systems. Compared to natural images, sonar images contain fewer texture details and are more susceptible to noise, making it difficult for non-experts to distinguish subtle differences between classes. This leads to their i

Cited by 0SourcePDFScholar
2025

DiffSim: Taming Diffusion Models for Evaluating Visual Similarity

ICCV 2025poster

Diffusion models have fundamentally transformed the field of generative models, making the assessment of similarity between customized model outputs and reference inputs critically important. However, traditional perceptual similarity metrics operate primarily at the pixel and patch levels, comparin…

2024

An Audio-Textual Diffusion Model for Converting Speech Signals into Ultrasound Tongue Imaging Data

ICASSP 2024accepted

Acoustic-to-articulatory inversion (AAI) is to convert audio into articulator movements, such as ultrasound tongue imaging (UTI) data. An issue of existing AAI methods is only using the personalized acoustic information to derive the general patterns of tongue motions, and thus the quality of genera…

Cited by 0SourceScholar
2023

Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk

ACL 2023long

Language is the principal tool for human communication, in which humor is one of the most attractive parts. Producing natural language like humans using computers, a.k.a, Natural Language Generation (NLG), has been widely used for dialogue systems, chatbots, machine translation, as well as computer-…

2023

Effective Open Intent Classification with K-center Contrastive Learning and Adjustable Decision Boundary

AAAI 2023technical

Open intent classification, which aims to correctly classify the known intents into their corresponding classes while identifying the new unknown (open) intents, is an essential but challenging task in dialogue systems. In this paper, we introduce novel K-center contrastive learning and adjustable d…

2023

Pseudo Multi-Source Domain Extension and Selective Pseudo-Labeling for Unsupervised Domain Adaptive Medical Image Segmentation

ICASSP 2023accepted

Unsupervised domain adaptation (UDA) attracts extra attention in medical image processing because no additional labels are required when adapting to different distributions. In this work, we propose a novel unsupervised domain adaptation framework named as Domain Expansion and PseudoLabeling (DEPL).…

Cited by 0SourceScholar
2023

Schema Inference for Interpretable Image Classification

ICLR 2023poster

In this paper, we study a novel inference paradigm, termed as schema inference, that learns to deductively infer the explainable predictions by rebuilding the prior deep neural network (DNN) forwarding scheme, guided by the prevalent philosophical cognitive concept of schema. We strive to reformulat…