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Found 11 papers, 4 papers with code
SACA Net: Cybersickness Assessment of Individual Viewers for VR Content via Graph-based Symptom Relation Embedding
In this paper, we propose a novel symptom-aware cybersickness assessment network (SACA Net) that quantifies physical symptom levels for assessing cybersickness of individual viewers.
Learning to Visually Localize Sound Sources from Mixtures without Prior Source Knowledge
In this paper, to overcome this limitation, we present a novel multi-sound source localization method that can perform localization without prior knowledge of the number of sound sources.
Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning
In addition, to alleviate the class imbalance problem, we introduce a new gradient similarity-based focal loss and adaptive feature scaling to ease overfitting to the major classes and underfitting to the minor classes.
Audio-Visual Spatial Integration and Recursive Attention for Robust Sound Source Localization
While the audio modality provides spatial cues to locate the sound source, existing approaches only use audio as an auxiliary role to compare spatial regions of the visual modality.
Faster Segment Anything: Towards Lightweight SAM for Mobile Applications
Concretely, we distill the knowledge from the heavy image encoder (ViT-H in the original SAM) to a lightweight image encoder, which can be automatically compatible with the mask decoder in the original SAM.
One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era
Overall, this work is the first to survey ChatGPT with a comprehensive review of its underlying technology, applications, and challenges.
Robust Small-Scale Pedestrian Detection With Cued Recall via Memory Learning
The purpose of the proposed large-scale embedding learning is to memorize and recall the large-scale pedestrian appearance via the LPR Memory.
Comprehensive Facial Expression Synthesis using Human-Interpretable Language
Recent advances in facial expression synthesis have shown promising results using diverse expression representations including facial action units.
Investigating Vulnerability to Adversarial Examples on Multimodal Data Fusion in Deep Learning
The success of multimodal data fusion in deep learning appears to be attributed to the use of complementary in-formation between multiple input data.
Revisiting Role of Autoencoders in Adversarial Settings
Through the comprehensive experimental results and analysis, this paper presents the inherent property of adversarial robustness in the autoencoders.
Iterative Deep Convolutional Encoder-Decoder Network for Medical Image Segmentation
In this paper, we propose a novel medical image segmentation using iterative deep learning framework.
