4 citations · 4 across the 9 of their papers we have counts for
11 papers
Physics-Guided Spectral Distillation for Underwater Image Enhancement on Resource-Constrained Devices
Yifan Chen, Kai He, Ye Zheng +3
Underwater image enhancement is crucial for improving visual perception in marine applications. Existing underwater image enhancement studies mainly focus on enhancement quality an…
Two-Stage Teacher-Student Reliable Prior Learning for Robust Underwater Image Enhancement
Yifan Chen, Jiaming Liu, Ye Zheng +2
Underwater image enhancement (UIE) aims to recover clear images from observations affected by wavelength-dependent absorption, scattering, and spatially nonuniform degradation. Alt…
Advancing Visual Reliability: Color-Accurate Underwater Image Enhancement for Real-Time Underwater Missions
Yiqiang Zhou, Yifan Chen, Zhe Sun +3
Underwater image enhancement plays a crucial role in providing reliable visual information for underwater platforms, since strong absorption and scattering in water-related environ…
Single-Pixel Vision-Language Model for Intrinsic Privacy-Preserving Behavioral Intelligence
Hongjun An, Yiliang Song, Jiawei Shao +2
Adverse social interactions, such as bullying, harassment, and other illicit activities, pose significant threats to individual well-being and public safety, leaving profound impac…
A Generative Data Framework with Authentic Supervision for Underwater Image Restoration and Enhancement
Yufeng Tian, Yifan Chen, Zhe Sun +5
Underwater image restoration and enhancement are crucial for correcting color distortion and restoring image details, thereby establishing a fundamental basis for subsequent underw…
Class-Aware Prototype Learning with Negative Contrast for Test-Time Adaptation of Vision-Language Models
Xiaozhen Qiao, Jingkai Zhao, Yuqiu Jiang +4
Vision-Language Models (VLMs) demonstrate impressive zero-shot generalization through large-scale image-text pretraining, yet their performance can drop once the deployment distrib…
Bidirectional Prototype-Reward co-Evolution for Test-Time Adaptation of Vision-Language Models
Xiaozhen Qiao, Peng Huang, Jiakang Yuan +6
Test-time adaptation (TTA) is crucial in maintaining performance of Vision Language Models (VLMs) when facing distribution shifts, particularly when the source data or target label…
ComKD-CLIP: Comprehensive Knowledge Distillation for Contrastive Language-Image Pre-traning Model
Yifan Chen, Xiaozhen Qiao, Zhe Sun +1
Contrastive Language-Image Pre-training (CLIP) models excel in integrating semantic information between images and text through contrastive learning techniques. It has achieved rem…
SentenceVAE: Enable Next-sentence Prediction for Large Language Models with Faster Speed, Higher Accuracy and Longer Context
Hongjun An, Yifan Chen, Zhe Sun +1
Current large language models (LLMs) primarily utilize next-token prediction method for inference, which significantly impedes their processing speed. In this paper, we introduce a…
CREST: Cross-modal Resonance through Evidential Deep Learning for Enhanced Zero-Shot Learning
Haojian Huang, Xiaozhen Qiao, Zhuo Chen +5
Zero-shot learning (ZSL) enables the recognition of novel classes by leveraging semantic knowledge transfer from known to unknown categories. This knowledge, typically encapsulated…
StreakNet-Arch: An Anti-scattering Network-based Architecture for Underwater Carrier LiDAR-Radar Imaging
Xuelong Li, Hongjun An, Haofei Zhao +6
In this paper, we introduce StreakNet-Arch, a real-time, end-to-end binary-classification framework based on our self-developed Underwater Carrier LiDAR-Radar (UCLR) that embeds Se…