Top Papers
google-research
google-research/google-research
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NeurIPS 2020
Google Research
Data Structures and Algorithms
Array Programming with NumPy
Array programming provides a powerful, compact, expressive syntax for accessing, manipulating, and operating on data in vectors, matrices, and higher-dimensional arrays.
Mathematical Software Computation
MediaPipe: A Framework for Building Perception Pipelines
google/mediapipe
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A developer can use MediaPipe to build prototypes by combining existing perception components, to advance them to polished cross-platform applications and measure system performance and resource consumption on target platforms.
Distributed, Parallel, and Cluster Computing
TDR-OBCA: A Reliable Planner for Autonomous Driving in Free-Space Environment
This paper presents an optimization-based collision avoidance trajectory generation method for autonomous driving in free-space environments, with enhanced robust-ness, driving comfort and efficiency.
Robotics
Manu: A Cloud Native Vector Database Management System
In the past three years, through interaction with our 1200+ industry users, we have sketched a vision for the features that next-generation vector databases should have, which include long-term evolvability, tunable consistency, good elasticity, and high performance.
Databases
PythonRobotics: a Python code collection of robotics algorithms
The focus of the project is on autonomous navigation, and the goal is for beginners in robotics to understand the basic ideas behind each algorithm.
Robotics
A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles
Self-driving vehicles are a maturing technology with the potential to reshape mobility by enhancing the safety, accessibility, efficiency, and convenience of automotive transportation.
Robotics
Incremental Sampling-based Algorithms for Optimal Motion Planning
Second, a new algorithm is considered, called the Rapidly-exploring Random Graph (RRG), and it is shown that the cost of the best path in the RRG converges to the optimum almost surely.
Robotics 68T40
Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
coqui-ai/TTS
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Several recent end-to-end text-to-speech (TTS) models enabling single-stage training and parallel sampling have been proposed, but their sample quality does not match that of two-stage TTS systems.
Sound Audio and Speech Processing
Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speech
coqui-ai/TTS
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Interspeech2020 2020
In this paper, we propose multi-band MelGAN, a much faster waveform generation model targeting to high-quality text-to-speech.
Sound Audio and Speech Processing
