419 citations · 512 across the 13 of their papers we have counts for
13 papers
Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action Recognition
Ming-Zhe Li, Zhen Jia, Zhang Zhang +2
Generalized zero-shot skeleton-based action recognition (GZSSAR) is a new challenging problem in computer vision community, which requires models to recognize actions without any t…
RAF: Holistic Compilation for Deep Learning Model Training
Cody Hao Yu, Haozheng Fan, Guangtai Huang +9
As deep learning is pervasive in modern applications, many deep learning frameworks are presented for deep learning practitioners to develop and train DNN models rapidly. Meanwhile…
Human Image Generation: A Comprehensive Survey
Zhen Jia, Zhang Zhang, Liang Wang +1
Image and video synthesis has become a blooming topic in computer vision and machine learning communities along with the developments of deep generative models, due to its great ac…
Lightweight Spatial-Channel Adaptive Coordination of Multilevel Refinement Enhancement Network for Image Reconstruction
Yuxi Cai, Huicheng Lai, Zhenghong Jia
Benefiting from the vigorous development of deep learning, many CNN-based image super-resolution methods have emerged and achieved better results than traditional algorithms. Howev…
Image Reconstruction of Multi Branch Feature Multiplexing Fusion Network with Mixed Multi-layer Attention
Yuxi Cai, Huicheng Lai
Image super-resolution reconstruction achieves better results than traditional methods with the help of the powerful nonlinear representation ability of convolution neural network.…
Focal and Efficient IOU Loss for Accurate Bounding Box Regression
Yi-Fan Zhang, Weiqiang Ren, Zhang Zhang +3
In object detection, bounding box regression (BBR) is a crucial step that determines the object localization performance. However, we find that most previous loss functions for BBR…
Data Motif-based Proxy Benchmarks for Big Data and AI Workloads
Wanling Gao, Jianfeng Zhan, Lei Wang +8
For the architecture community, reasonable simulation time is a strong requirement in addition to performance data accuracy. However, emerging big data and AI workloads are too hug…
Data Motifs: A Lens Towards Fully Understanding Big Data and AI Workloads
Wanling Gao, Jianfeng Zhan, Lei Wang +9
The complexity and diversity of big data and AI workloads make understanding them difficult and challenging. This paper proposes a new approach to modelling and characterizing big…
Data Dwarfs: A Lens Towards Fully Understanding Big Data and AI Workloads
Wanling Gao, Jianfeng Zhan, Lei Wang +6
The complexity and diversity of big data and AI workloads make understanding them difficult and challenging. This paper proposes a new approach to characterizing big data and AI wo…
A Dwarf-based Scalable Big Data Benchmarking Methodology
Wanling Gao, Lei Wang, Jianfeng Zhan +7
Different from the traditional benchmarking methodology that creates a new benchmark or proxy for every possible workload, this paper presents a scalable big data benchmarking meth…
Characterization and Architectural Implications of Big Data Workloads
Lei Wang, Jianfeng Zhan, Zhen Jia +1
Big data areas are expanding in a fast way in terms of increasing workloads and runtime systems, and this situation imposes a serious challenge to workload characterization, which…
Understanding Big Data Analytic Workloads on Modern Processors
Zhen Jia, Lei Wang, Jianfeng Zhan +3
Big data analytics applications play a significant role in data centers, and hence it has become increasingly important to understand their behaviors in order to further improve th…
BigDataBench: a Big Data Benchmark Suite from Internet Services
Lei Wang, Jianfeng Zhan, Chunjie Luo +12
As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these…