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Found 23 papers, 9 papers with code
Interactive Image Synthesis with Panoptic Layout Generation
In particular, the stuff layouts can take amorphous shapes and fill up the missing regions left out by the instance layouts.
Onsite Non-Line-of-Sight Imaging via Online Calibrations
There has been an increasing interest in deploying non-line-of-sight (NLOS) imaging systems for recovering objects behind an obstacle.
Self-adaptive Multi-task Particle Swarm Optimization
In the focus search strategy, if there is no knowledge source benefit the optimization of a task, then all knowledge sources in the task's pool are forbidden to be utilized except the task, which helps to improve the performance of the proposed algorithm.
Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding
Instead, from a perspective on temporal grounding as a metric-learning problem, we present a Mutual Matching Network (MMN), to directly model the similarity between language queries and video moments in a joint embedding space.
Fine-Grained Shape-Appearance Mutual Learning for Cloth-Changing Person Re-Identification
Recently, person re-identification (Re-ID) has achieved great progress.
Microsoft Recommenders: Tools to Accelerate Developing Recommender Systems
The purpose of this work is to highlight the content of the Microsoft Recommenders repository and show how it can be used to reduce the time involved in developing recommender systems.
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval
In light of these problems, we observed that most online content platforms have both a search and a recommender system that, while having heterogeneous input spaces, can be connected through their common output item space and a shared semantic representation.
Drosophila-Inspired 3D Moving Object Detection Based on Point Clouds
3D moving object detection is one of the most critical tasks in dynamic scene analysis.
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning
Structured convex optimization on weighted graphs finds numerous applications in machine learning and computer vision.
Modeling Information Need of Users in Search Sessions
Users issue queries to Search Engines, and try to find the desired information in the results produced.
Informative GANs via Structured Regularization of Optimal Transport
We tackle the challenge of disentangled representation learning in generative adversarial networks (GANs) from the perspective of regularized optimal transport (OT).
Variational Uncalibrated Photometric Stereo under General Lighting
Photometric stereo (PS) techniques nowadays remain constrained to an ideal laboratory setup where modeling and calibration of lighting is amenable.
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems
In this work, we consider nonconvex composite problems that involve inf-convolution with a Legendre function, which gives rise to an anisotropic generalization of the proximal mapping and Moreau-envelope.
Probabilistic Discriminative Learning with Layered Graphical Models
Probabilistic graphical models are traditionally known for their successes in generative modeling.
Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform
Dense pixelwise prediction such as semantic segmentation is an up-to-date challenge for deep convolutional neural networks (CNNs).
Network Reconstruction and Controlling Based on Structural Regularity Analysis
In addition, the model is capable of measuring the importance of microscopic network elements, i. e., nodes and links, in terms of network regularity thereby allowing us to regulate the reconstructability of networks based on them.
Combinatorial Preconditioners for Proximal Algorithms on Graphs
We present a novel preconditioning technique for proximal optimization methods that relies on graph algorithms to construct effective preconditioners.
LED-based Photometric Stereo: Modeling, Calibration and Numerical Solution
The second one directly recovers the depth, by formulating photometric stereo as a system of PDEs which are partially linearized using image ratios.
A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting
This paper tackles the photometric stereo problem in the presence of inaccurate lighting, obtained either by calibration or by an uncalibrated photometric stereo method.
Retrospective Higher-Order Markov Processes for User Trails
In this paper we propose the retrospective higher-order Markov process (RHOMP) as a low-parameter model for such sequences.
General Tensor Spectral Co-clustering for Higher-Order Data
Spectral clustering and co-clustering are well-known techniques in data analysis, and recent work has extended spectral clustering to square, symmetric tensors and hypermatrices derived from a network.
Multi-way Monte Carlo Method for Linear Systems
A sufficient condition for the method to work is $\| H \| < 1$, which greatly limits the usability of this method.
Pure Price of Anarchy for Generalized Second Price Auction
Previous studies have shown that the pure Price Of Anarchy (POA) of GSP is 1. 25 when there are two ad slots and 1. 259 when three ad slots.
Computer Science and Game Theory
