Search Results for author:
Found 18 papers, 13 papers with code
GeoTransformer: Fast and Robust Point Cloud Registration with Geometric Transformer
They seek correspondences over downsampled superpoints, which are then propagated to dense points.
Ranked #5 on
Point Cloud Registration
on FP-O-H
Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration
We first design a local spatial consistency measure over the deformation graph of the point cloud, which evaluates the spatial compatibility only between the correspondences in the vicinity of a graph node.
Wound Segmentation with Dynamic Illumination Correction and Dual-view Semantic Fusion
Wound image segmentation is a critical component for the clinical diagnosis and in-time treatment of wounds.
Unsupervised Voice-Face Representation Learning by Cross-Modal Prototype Contrast
We present an approach to learn voice-face representations from the talking face videos, without any identity labels.
Geometric Transformer for Fast and Robust Point Cloud Registration
Such sparse and loose matching requires contextual features capturing the geometric structure of the point clouds.
Audio Tagging by Cross Filtering Noisy Labels
Yet, it is labor-intensive to accurately annotate large amount of audio data, and the dataset may contain noisy labels in the practical settings.
A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning
Rapid progress has been made in the field of reading comprehension and question answering, where several systems have achieved human parity in some simplified settings.
Ranked #8 on
Question Answering
on DROP Test
Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension
This paper considers the reading comprehension task in which multiple documents are given as input.
Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification
Open-domain targeted sentiment analysis aims to detect opinion targets along with their sentiment polarities from a sentence.
Aspect-Based Sentiment Analysis (ABSA)
Aspect Term Extraction and Sentiment Classification
+2
ThunderNet: Towards Real-time Generic Object Detection
In this paper, we investigate the effectiveness of two-stage detectors in real-time generic detection and propose a lightweight two-stage detector named ThunderNet.
Ranked #15 on
Object Detection
on PASCAL VOC 2007
Attention-Guided Answer Distillation for Machine Reading Comprehension
Despite that current reading comprehension systems have achieved significant advancements, their promising performances are often obtained at the cost of making an ensemble of numerous models.
Read + Verify: Machine Reading Comprehension with Unanswerable Questions
Machine reading comprehension with unanswerable questions aims to abstain from answering when no answer can be inferred.
Ranked #11 on
Question Answering
on SQuAD2.0 dev
Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions
Depthwise convolutions provide significant performance benefits owing to the reduction in both parameters and mult-adds.
Learning Environmental Sounds with Multi-scale Convolutional Neural Network
For leveraging the waveform-based features and spectrogram-based features in a single model, we introduce two-phase method to fuse the different features.
Sound Audio and Speech Processing
Merging and Evolution: Improving Convolutional Neural Networks for Mobile Applications
Compact neural networks are inclined to exploit "sparsely-connected" convolutions such as depthwise convolution and group convolution for employment in mobile applications.
FD-MobileNet: Improved MobileNet with a Fast Downsampling Strategy
Experiments on ILSVRC 2012 and PASCAL VOC 2007 datasets demonstrate that FD-MobileNet consistently outperforms MobileNet and achieves comparable results with ShuffleNet under different computational budgets, for instance, surpassing MobileNet by 5. 5% on the ILSVRC 2012 top-1 accuracy and 3. 6% on the VOC 2007 mAP under a complexity of 12 MFLOPs.
Reinforced Mnemonic Reader for Machine Reading Comprehension
In this paper, we introduce the Reinforced Mnemonic Reader for machine reading comprehension tasks, which enhances previous attentive readers in two aspects.
Ranked #17 on
Question Answering
on SQuAD1.1 dev
hi-RF: Incremental Learning Random Forest for large-scale multi-class Data Classification
Most traditional methods struggle to balance the precision and computational burden when data and its number of classes increased.
