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Found 13 papers, 3 papers with code
Transparent Object Depth Completion
The perception of transparent objects for grasp and manipulation remains a major challenge, because existing robotic grasp methods which heavily rely on depth maps are not suitable for transparent objects due to their unique visual properties.
TransFR: Transferable Federated Recommendation with Pre-trained Language Models
To this end, we propose a transferable federated recommendation model with universal textual representations, TransFR, which delicately incorporates the general capabilities empowered by pre-trained language models and the personalized abilities by fine-tuning local private data.
HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection
An individualised head-related transfer function (HRTF) is very important for creating realistic virtual reality (VR) and augmented reality (AR) environments.
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition
To facilitate research in the direction of fine-tuning foundation models from human feedback, we held the MineRL BASALT Competition on Fine-Tuning from Human Feedback at NeurIPS 2022.
KinD-LCE Curve Estimation And Retinex Fusion On Low-Light Image
The proposed method, KinD-LCE, uses a light curve estimation module to enhance the illumination map in the Retinex decomposed image, improving the overall image brightness.
Accurate Virus Identification with Interpretable Raman Signatures by Machine Learning
We present such a machine learning approach for analyzing Raman spectra of human and avian viruses.
Multimodal Dual Emotion with Fusion of Visual Sentiment for Rumor Detection
In recent years, rumors have had a devastating impact on society, making rumor detection a significant challenge.
Deep Probabilistic Graph Matching
Most previous learning-based graph matching algorithms solve the \textit{quadratic assignment problem} (QAP) by dropping one or more of the matching constraints and adopting a relaxed assignment solver to obtain sub-optimal correspondences.
GLAN: A Graph-based Linear Assignment Network
The experimental results on a synthetic dataset reveal that our method outperforms state-of-the-art baselines and achieves consistently high accuracy with the increment of the problem size.
Joint Graph Learning and Matching for Semantic Feature Correspondence
In this paper, we propose a joint \emph{graph learning and matching} network, named GLAM, to explore reliable graph structures for boosting graph matching.
Target-specified Sequence Labeling with Multi-head Self-attention for Target-oriented Opinion Words Extraction
Many recent works on ABSA focus on Target-oriented Opinion Words (or Terms) Extraction (TOWE), which aims at extracting the corresponding opinion words for a given opinion target.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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GM-MLIC: Graph Matching based Multi-Label Image Classification
Multi-Label Image Classification (MLIC) aims to predict a set of labels that present in an image.
Graphical Models for Financial Time Series and Portfolio Selection
We examine a variety of graphical models to construct optimal portfolios.
