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Found 21 papers, 5 papers with code
Sparse Tensor-based Multiscale Representation for Point Cloud Geometry Compression
This study develops a unified Point Cloud Geometry (PCG) compression method through Sparse Tensor Processing (STP) based multiscale representation of voxelized PCG, dubbed as the SparsePCGC.
Improving Prosody for Unseen Texts in Speech Synthesis by Utilizing Linguistic Information and Noisy Data
Recent advancements in end-to-end speech synthesis have made it possible to generate highly natural speech.
Sharp Analysis of Random Fourier Features in Classification
Utilizing the regularity condition, we show for the first time that random Fourier features classification can achieve $O(1/\sqrt{n})$ learning rate with only $\Omega(\sqrt{n} \log n)$ features, as opposed to $\Omega(n)$ features suggested by previous results.
No-Reference Image Quality Assessment by Hallucinating Pristine Features
In this paper, we propose a no-reference (NR) image quality assessment (IQA) method via feature level pseudo-reference (PR) hallucination.
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification
In this paper, we propose a transfer-learning based model construction technique for the aerial scene classification problem.
Ranked #1 on
Aerial Scene Classification
on AID (20% as trainset)
Towards an Understanding of Benign Overfitting in Neural Networks
Modern machine learning models often employ a huge number of parameters and are typically optimized to have zero training loss; yet surprisingly, they possess near-optimal prediction performance, contradicting classical learning theory.
Effective Subspace Indexing via Interpolation on Stiefel and Grassmann manifolds
We propose a novel local Subspace Indexing Model with Interpolation (SIM-I) for low-dimensional embedding of image datasets.
Multiscale Point Cloud Geometry Compression
Recent years have witnessed the growth of point cloud based applications because of its realistic and fine-grained representation of 3D objects and scenes.
Dense-View GEIs Set: View Space Covering for Gait Recognition based on Dense-View GAN
In this paper, we, therefore, introduce a Dense-View GEIs Set (DV-GEIs) to deal with the challenge of limited view angles.
Benign Overfitting and Noisy Features
Modern machine learning often operates in the regime where the number of parameters is much higher than the number of data points, with zero training loss and yet good generalization, thereby contradicting the classical bias-variance trade-off.
Inferring Point Cloud Quality via Graph Similarity
We propose the GraphSIM -- an objective metric to accurately predict the subjective quality of point cloud with superimposed geometry and color impairments.
Hyperspectral Image Classification with Attention Aided CNNs
Specifically, a spectral attention sub-network and a spatial attention sub-network are proposed for spectral and spatial classification, respectively.
Classification Of Hyperspectral Images
General Classification
+1
Dual Temporal Memory Network for Efficient Video Object Segmentation
We present an end-to-end network which stores short- and long-term video sequence information preceding the current frame as the temporal memories to address the temporal modeling in VOS.
One-shot visual object segmentation
Semantic Segmentation
+2
Classification of Hyperspectral and LiDAR Data Using Coupled CNNs
For the feature-level fusion, three different fusion strategies are evaluated, including the concatenation strategy, the maximization strategy, and the summation strategy.
Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic Fairness
We present a regularization approach to this problem that trades off predictive accuracy of the learned models (with respect to biased labels) for the fairness in terms of statistical parity, i. e. independence of the decisions from the sensitive covariates.
Residual-Guided In-Loop Filter Using Convolution Neural Network
The block-based coding structure in the hybrid video coding framework inevitably introduces compression artifacts such as blocking, ringing, etc.
Deep AutoEncoder-based Lossy Geometry Compression for Point Clouds
Point cloud is a fundamental 3D representation which is widely used in real world applications such as autonomous driving.
Towards A Unified Analysis of Random Fourier Features
We study both the standard random Fourier features method for which we improve the existing bounds on the number of features required to guarantee the corresponding minimax risk convergence rate of kernel ridge regression, as well as a data-dependent modification which samples features proportional to \emph{ridge leverage scores} and further reduces the required number of features.
Hybrid Point Cloud Attribute Compression Using Slice-based Layered Structure and Block-based Intra Prediction
In intra-frame compression of point cloud color attributes, results demonstrate that our method performs better than the state-of-the-art region-adaptive hierarchical transform (RAHT) system, and on average a 29. 37$\%$ BD-rate gain is achieved.
Multimedia
Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach
Emotion recognition from facial expressions is tremendously useful, especially when coupled with smart devices and wireless multimedia applications.
Projection based advanced motion model for cubic mapping for 360-degree video
This paper proposes a novel advanced motion model to handle the irregular motion for the cubic map projection of 360-degree video.
