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Found 20 papers, 10 papers with code
READ: Large-Scale Neural Scene Rendering for Autonomous Driving
In this paper, a large-scale neural rendering method is proposed to synthesize the autonomous driving scene~(READ), which makes it possible to synthesize large-scale driving scenarios on a PC through a variety of sampling schemes.
Ranked #1 on
Novel View Synthesis
on KITTI
Hybrid Reasoning Network for Video-based Commonsense Captioning
Firstly, we develop multi-commonsense learning for semantic-level reasoning by jointly training different commonsense types in a unified network, which encourages the interaction between the clues of multiple commonsense descriptions, event-wise captions and videos.
Content-Augmented Feature Pyramid Network with Light Linear Spatial Transformers for Object Detection
As one of the prevalent components, Feature Pyramid Network (FPN) is widely used in current object detection models for improving multi-scale object detection performance.
Minimal Cycle Representatives in Persistent Homology using Linear Programming: an Empirical Study with User's Guide
Cycle representatives of persistent homology classes can be used to provide descriptions of topological features in data.
Rademacher complexity of noisy quantum circuits
Noise in quantum systems is a major obstacle to implementing many quantum algorithms on large quantum circuits.
Quantum Physics
Effects of quantum resources on the statistical complexity of quantum circuits
We investigate how the addition of quantum resources changes the statistical complexity of quantum circuits by utilizing the framework of quantum resource theories.
On the statistical complexity of quantum circuits
In this work, we apply a particular measure of statistical complexity, namely the Rademacher complexity, to the quantum circuit model in quantum computation and study how the statistical complexity depends on various quantum circuit parameters.
PSGCNet: A Pyramidal Scale and Global Context Guided Network for Dense Object Counting in Remote Sensing Images
Object counting, which aims to count the accurate number of object instances in images, has been attracting more and more attention.
Robust Gaussian Process Regression Based on Iterative Trimming
The Gaussian process (GP) regression can be severely biased when the data are contaminated by outliers.
OCNLI: Original Chinese Natural Language Inference
In this paper, we present the first large-scale NLI dataset (consisting of ~56, 000 annotated sentence pairs) for Chinese called the Original Chinese Natural Language Inference dataset (OCNLI).
Organ size increases with obesity and correlates with cancer risk
Obesity increases significantly cancer risk in various organs.
CLUE: A Chinese Language Understanding Evaluation Benchmark
The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks.
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese.
How to Evaluate the Next System: Automatic Dialogue Evaluation from the Perspective of Continual Learning
Automatic dialogue evaluation plays a crucial role in open-domain dialogue research.
Learning Spatiotemporal Features of Ride-sourcing Services with Fusion Convolutional Network
To collectively forecast the demand for ride-sourcing services in all regions of a city, the deep learning approaches have been applied with commendable results.
A Multi-Domain Feature Learning Method for Visual Place Recognition
Visual Place Recognition (VPR) is an important component in both computer vision and robotics applications, thanks to its ability to determine whether a place has been visited and where specifically.
MRS-VPR: a multi-resolution sampling based global visual place recognition method
We propose MRS-VPR, a multi-resolution, sampling-based place recognition method, which can significantly improve the matching efficiency and accuracy in sequential matching.
Observation data pre-processing and scientific data products generation of POLAR
This pipeline has been successfully applied for the use by the POLAR Science Data Center in IHEP after POLAR was launched and switched on.
Instrumentation and Methods for Astrophysics High Energy Physics - Experiment Data Analysis, Statistics and Probability
Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network
Human generates responses relying on semantic and functional dependencies, including coreference relation, among dialogue elements and their context.
Ranked #6 on
Conversational Response Selection
on RRS
In-Orbit Instrument Performance Study and Calibration for POLAR Polarization Measurements
POLAR is a compact space-borne detector designed to perform reliable measurements of the polarization for transient sources like Gamma-Ray Bursts in the energy range 50-500keV.
Instrumentation and Methods for Astrophysics High Energy Physics - Experiment Instrumentation and Detectors
