Iterative Experience Refinement of Software-Developing Agents

1 code implementation • 7 May 2024 • Chen Qian, Jiahao Li, Yufan Dang, Wei Liu, Yifei Wang, Zihao Xie, Weize Chen, Cheng Yang, Yingli Zhang, Zhiyuan Liu, Maosong Sun

We propose two fundamental patterns: the successive pattern, refining based on nearest experiences within a task batch, and the cumulative pattern, acquiring experiences across all previous task batches.

IoU-uniform R-CNN: Breaking Through the Limitations of RPN

1 code implementation • 11 Dec 2019 • Li Zhu, Zihao Xie, Liman Liu, Bo Tao, Wenbing Tao

Region Proposal Network (RPN) is the cornerstone of two-stage object detectors, it generates a sparse set of object proposals and alleviates the extrem foregroundbackground class imbalance problem during training.

Object object-detection +2

Localization-aware Channel Pruning for Object Detection

no code implementations • 6 Nov 2019 • Zihao Xie, Wenbing Tao, Li Zhu, Lin Zhao

In this paper, based on discrimination-aware channel pruning (DCP) which is state-of-the-art pruning method for classification, we propose a localization-aware auxiliary network to find out the channels with key information for classification and regression so that we can conduct channel pruning directly for object detection, which saves lots of time and computing resources.

Classification General Classification +5