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Deep Lookup Network
Yulan Guo, Longguang Wang, Wendong Mao +4
Convolutional neural networks are constructed with massive operations with different types and are highly computationally intensive. Among these operations, multiplication operatio…
StripDet: Strip Attention-Based Lightweight 3D Object Detection from Point Cloud
Weichao Wang, Wendong Mao, Zhongfeng Wang
The deployment of high-accuracy 3D object detection models from point cloud remains a significant challenge due to their substantial computational and memory requirements. To addre…
A Memory-Efficient Framework for Deformable Transformer with Neural Architecture Search
Wendong Mao, Mingfan Zhao, Jianfeng Guan +2
Deformable Attention Transformers (DAT) have shown remarkable performance in computer vision tasks by adaptively focusing on informative image regions. However, their data-dependen…
CDM-QTA: Quantized Training Acceleration for Efficient LoRA Fine-Tuning of Diffusion Model
Jinming Lu, Minghao She, Wendong Mao +1
Fine-tuning large diffusion models for custom applications demands substantial power and time, which poses significant challenges for efficient implementation on mobile devices. In…
An Efficient Sparse Hardware Accelerator for Spike-Driven Transformer
Zhengke Li, Wendong Mao, Siyu Zhang +2
Recently, large models, such as Vision Transformer and BERT, have garnered significant attention due to their exceptional performance. However, their extensive computational requir…