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Found 11 papers, 5 papers with code
Dual Encoder: Exploiting the Potential of Syntactic and Semantic for Aspect Sentiment Triplet Extraction
In this work, we propose a \emph{Dual Encoder: Exploiting the potential of Syntactic and Semantic} model (D2E2S), which maximizes the syntactic and semantic relationships among words.
Extensible Multi-Granularity Fusion Network for Aspect-based Sentiment Analysis
This paper presents the Extensible Multi-Granularity Fusion (EMGF) network, which integrates information from dependency and constituent syntactic, attention semantic , and external knowledge graphs.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
LSwinSR: UAV Imagery Super-Resolution based on Linear Swin Transformer
Super-resolution, which aims to reconstruct high-resolution images from low-resolution images, has drawn considerable attention and has been intensively studied in computer vision and remote sensing communities.
GMF: General Multimodal Fusion Framework for Correspondence Outlier Rejection
In this paper, we propose General Multimodal Fusion (GMF) to learn to reject the correspondence outliers by leveraging both the structure and texture information.
Revisiting Open World Object Detection
Open World Object Detection (OWOD), simulating the real dynamic world where knowledge grows continuously, attempts to detect both known and unknown classes and incrementally learn the identified unknown ones.
IMFNet: Interpretable Multimodal Fusion for Point Cloud Registration
In this paper, we propose a new multimodal fusion method to generate a point cloud registration descriptor by considering both structure and texture information.
Ranked #1 on
Point Cloud Registration
on 3DMatch Benchmark
(using extra training data)
Simplifying Reinforced Feature Selection via Restructured Choice Strategy of Single Agent
To address the question, we develop a single-agent reinforced feature selection approach integrated with restructured choice strategy.
Multi-modal Aggregation for Video Classification
In this paper, we present a solution to Large-Scale Video Classification Challenge (LSVC2017) [1] that ranked the 1st place.
Conditional Convolutional Neural Network for Modality-Aware Face Recognition
Faces in the wild are usually captured with various poses, illuminations and occlusions, and thus inherently multimodally distributed in many tasks.
Bi-label Propagation for Generic Multiple Object Tracking
In this paper, we propose a label propagation framework to handle the multiple object tracking (MOT) problem for a generic object type (cf.
Unified Face Analysis by Iterative Multi-Output Random Forests
In this paper, we present a unified method for joint face image analysis, i. e., simultaneously estimating head pose, facial expression and landmark positions in real-world face images.
