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Found 20 papers, 5 papers with code
S3: Learnable Sparse Signal Superdensity for Guided Depth Estimation
Dense depth estimation plays a key role in multiple applications such as robotics, 3D reconstruction, and augmented reality.
$S^3$: Learnable Sparse Signal Superdensity for Guided Depth Estimation
Dense depth estimation plays a key role in multiple applications such as robotics, 3D reconstruction, and augmented reality.
What Do Position Embeddings Learn? An Empirical Study of Pre-Trained Language Model Positional Encoding
This paper focuses on providing a new insight of pre-trained position embeddings through feature-level analysis and empirical experiments on most of iconic NLP tasks.
Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
In this paper, we design a simple and efficient embedding algorithm that learns a small set of anchor embeddings and a sparse transformation matrix.
Last-mile Delivery: Optimal Locker Location Under Multinomial Logit Choice Model
Motivated by a real case in Singapore, we consider a POP-Locker Alliance who operates a set of POP-stations and wishes to improve the last-mile delivery by opening new locker facilities.
Optimization and Control
Finding Optimal Points for Expensive Functions Using Adaptive RBF-Based Surrogate Model Via Uncertainty Quantification
Then it utilizes a model-guided selection criterion to identify a new point from a candidate set for function evaluation.
Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity
Encoding models based on task features predict activity in different regions across the whole brain.
PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation
This linear model is then utilized to reduce the redundant information in the left and right road images.
Entire Space Multi-Task Modeling via Post-Click Behavior Decomposition for Conversion Rate Prediction
Although existing methods, typically built on the user sequential behavior path ``impression$\to$click$\to$purchase'', is effective for dealing with SSB issue, they still struggle to address the DS issue due to rare purchase training samples.
PointIT: A Fast Tracking Framework Based on 3D Instance Segmentation
Finally, we extend the Sort algorithm with this instance framework to realize tracking in the 3D LiDAR point cloud data.
Modeling Melodic Feature Dependency with Modularized Variational Auto-Encoder
Automatic melody generation has been a long-time aspiration for both AI researchers and musicians.
Focal Loss in 3D Object Detection
Inspired by the recent use of focal loss in image-based object detection, we extend this hard-mining improvement of binary cross entropy to point-cloud-based object detection and conduct experiments to show its performance based on two different 3D detectors: 3D-FCN and VoxelNet.
A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors
We normalize the data and perimeter terms in the functional to expedite the graph cut without having to optimize the scaling parameter $\lambda$.
PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point Cloud
We take the spherical image, which is transformed from the 3D LiDAR point clouds, as input of the convolutional neural networks (CNNs) to predict the point-wise semantic map.
State Space LSTM Models with Particle MCMC Inference
Long Short-Term Memory (LSTM) is one of the most powerful sequence models.
Predicting Restaurant Consumption Level through Social Media Footprints
Accurate prediction of user attributes from social media is valuable for both social science analysis and consumer targeting.
Measuring Asymmetric Opinions on Online Social Interrelationship with Language and Network Features
Instead of studying the properties of social relationship from an objective view, in this paper, we focus on individuals' subjective and asymmetric opinions on their interrelationships.
Structure vs. Language: Investigating the Multi-factors of Asymmetric Opinions on Online Social Interrelationship with a Case Study
With statistical analysis on Enron email dataset, we find that individuals' opinions (measured by interactive language features) on their interrelationship are related to some of their important structural context in social network.
Heart Rate Variability and Respiration Signal as Diagnostic Tools for Late Onset Sepsis in Neonatal Intensive Care Units
The objective of this paper was to determine if HRV, respiration and their relationships help to diagnose infection in premature infants via non-invasive ways in NICU.
