9 citations · 10 across the 11 of their papers we have counts for
11 papers
Towards Generalizable Deepfake Detection via Real Distribution Bias Correction
Ming-Hui Liu, Harry Cheng, Xin Luo +2
To generalize deepfake detectors to future unseen forgeries, most existing methods attempt to simulate the dynamically evolving forgery types using available source domain data. Ho…
Progressively Exploring and Exploiting Inference Data to Break Fine-Grained Classification Barrier
Li-Jun Zhao, Si-Yuan Zhang, Zhen-Duo Chen +2
Current fine-grained classification research primarily focuses on fine-grained feature learning. However, in real-world scenarios, fine-grained data annotation is challenging, and…
EVC-MF: End-to-end Video Captioning Network with Multi-scale Features
Tian-Zi Niu, Zhen-Duo Chen, Xin Luo +1
Conventional approaches for video captioning leverage a variety of offline-extracted features to generate captions. Despite the availability of various offline-feature-extractors t…
High-level Codes and Fine-grained Weights for Online Multi-modal Hashing Retrieval
Yu-Wei Zhan, Xiao-Ming Wu, Xin Luo +2
In the real world, multi-modal data often appears in a streaming fashion, and there is a growing demand for similarity retrieval from such non-stationary data, especially at a larg…
Bias Mitigating Few-Shot Class-Incremental Learning
Li-Jun Zhao, Zhen-Duo Chen, Zi-Chao Zhang +2
Few-shot class-incremental learning (FSCIL) aims at recognizing novel classes continually with limited novel class samples. A mainstream baseline for FSCIL is first to train the wh…
Federated Class-Incremental Learning with Prompting
Xin Luo, Fang-Yi Liang, Jiale Liu +3
As Web technology continues to develop, it has become increasingly common to use data stored on different clients. At the same time, federated learning has received widespread atte…
FedVMR: A New Federated Learning method for Video Moment Retrieval
Yan Wang, Xin Luo, Zhen-Duo Chen +3
Despite the great success achieved, existing video moment retrieval (VMR) methods are developed under the assumption that data are centralizedly stored. However, in real-world appl…
Asymmetric Modality Translation For Face Presentation Attack Detection
Zhi Li, Haoliang Li, Xin Luo +3
Face presentation attack detection (PAD) is an essential measure to protect face recognition systems from being spoofed by malicious users and has attracted great attention from bo…
Online Enhanced Semantic Hashing: Towards Effective and Efficient Retrieval for Streaming Multi-Modal Data
Xiao-Ming Wu, Xin Luo, Yu-Wei Zhan +3
With the vigorous development of multimedia equipment and applications, efficient retrieval of large-scale multi-modal data has become a trendy research topic. Thereinto, hashing h…
Weakly-Supervised Online Hashing
Yu-Wei Zhan, Xin Luo, Yu Sun +3
With the rapid development of social websites, recent years have witnessed an explosive growth of social images with user-provided tags which continuously arrive in a streaming fas…
Measuring the Accuracy of Object Detectors and Trackers
Tobias Bottger, Patrick Follmann, Michael Fauser
The accuracy of object detectors and trackers is most commonly evaluated by the Intersection over Union (IoU) criterion. To date, most approaches are restricted to axis-aligned or…