most citedLearning Modulated Loss for Rotated Object Detection

63 citations · 76 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20207 cited

Learning Structured Communication for Multi-agent Reinforcement Learning

Junjie Sheng, Xiangfeng Wang, Bo Jin +5

This work explores the large-scale multi-agent communication mechanism under a multi-agent reinforcement learning (MARL) setting. We summarize the general categories of topology fo…

cs.CV201963 cited

Learning Modulated Loss for Rotated Object Detection

Wen Qian, Xue Yang, Silong Peng +2

Popular rotated detection methods usually use five parameters (coordinates of the central point, width, height, and rotation angle) to describe the rotated bounding box and l1-loss…

q-bio.NC2019

Decoding Spiking Mechanism with Dynamic Learning on Neuron Population

Zhijie Chen, Junchi Yan, Longyuan Li +1

A main concern in cognitive neuroscience is to decode the overt neural spike train observations and infer latent representations under neural circuits. However, traditional methods…

cs.LG2019

Heterogeneous Graph-based Knowledge Transfer for Generalized Zero-shot Learning

Junjie Wang, Xiangfeng Wang, Bo Jin +3

Generalized zero-shot learning (GZSL) tackles the problem of learning to classify instances involving both seen classes and unseen ones. The key issue is how to effectively transfe…

cs.LG20196 cited

Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling

Qitian Wu, Zixuan Zhang, Xiaofeng Gao +2

We target modeling latent dynamics in high-dimension marked event sequences without any prior knowledge about marker relations. Such problem has been rarely studied by previous wor…