36 citations · 50 across the 9 of their papers we have counts for
9 papers
Ex3: Automatic Novel Writing by Extracting, Excelsior and Expanding
Lei Huang, Jiaming Guo, Guanhua He +5
Generating long-term texts such as novels using artificial intelligence has always been a challenge. A common approach is to use large language models (LLMs) to construct a hierarc…
Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 challenge: Report
Andrey Ignatov, Radu Timofte, Cheng-Ming Chiang +50
Video super-resolution is one of the most popular tasks on mobile devices, being widely used for an automatic improvement of low-bitrate and low-resolution video streams. While num…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…
Distilling Object Detectors with Feature Richness
Zhixing Du, Rui Zhang, Ming Chang +4
In recent years, large-scale deep models have achieved great success, but the huge computational complexity and massive storage requirements make it a great challenge to deploy the…
Domain-Specific Suppression for Adaptive Object Detection
Yu Wang, Rui Zhang, Shuo Zhang +4
Domain adaptation methods face performance degradation in object detection, as the complexity of tasks require more about the transferability of the model. We propose a new perspec…
DWM: A Decomposable Winograd Method for Convolution Acceleration
Di Huang, Xishan Zhang, Rui Zhang +9
Winograd's minimal filtering algorithm has been widely used in Convolutional Neural Networks (CNNs) to reduce the number of multiplications for faster processing. However, it is on…
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers
Xishan Zhang, Shaoli Liu, Rui Zhang +8
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers. Recent emerged quantization technique has been applied to inference of deep neur…
BENCHIP: Benchmarking Intelligence Processors
Jinhua Tao, Zidong Du, Qi Guo +12
The increasing attention on deep learning has tremendously spurred the design of intelligence processing hardware. The variety of emerging intelligence processors requires standard…
Global Adaptive Routing Algorithm Without Additional Congestion Propagation Network
Shaoli Liu, Yunji Chen, Tianshi Chen +2
Adaptive routing algorithm has been employed in multichip interconnection networks in order to improve network performance. Does a algorithm use local or global network state? This…