278 citations · 631 across the 31 of their papers we have counts for
46 papers · 1 filter
GhostNetV3: Exploring the Training Strategies for Compact Models
Zhenhua Liu, Zhiwei Hao, Kai Han +2
Compact neural networks are specially designed for applications on edge devices with faster inference speed yet modest performance. However, training strategies of compact models a…
An Empirical Study of Scaling Law for OCR
Miao Rang, Zhenni Bi, Chuanjian Liu +2
The laws of model size, data volume, computation and model performance have been extensively studied in the field of Natural Language Processing (NLP). However, the scaling laws in…
One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation
Zhiwei Hao, Jianyuan Guo, Kai Han +4
Knowledge distillation~(KD) has proven to be a highly effective approach for enhancing model performance through a teacher-student training scheme. However, most existing distillat…
Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism
Chengcheng Wang, Wei He, Ying Nie +4
In the past years, YOLO-series models have emerged as the leading approaches in the area of real-time object detection. Many studies pushed up the baseline to a higher level by mod…
Category Feature Transformer for Semantic Segmentation
Quan Tang, Chuanjian Liu, Fagui Liu +5
Aggregation of multi-stage features has been revealed to play a significant role in semantic segmentation. Unlike previous methods employing point-wise summation or concatenation f…
Less is More: Focus Attention for Efficient DETR
Dehua Zheng, Wenhui Dong, Hailin Hu +2
DETR-like models have significantly boosted the performance of detectors and even outperformed classical convolutional models. However, all tokens are treated equally without discr…