LoOp: Looking for Optimal Hard Negative Embeddings for Deep Metric Learning

20 August 2021

Papers citing "LoOp: Looking for Optimal Hard Negative Embeddings for Deep Metric Learning"

7 / 7 papers shown

Title
Improved Diversity-Promoting Collaborative Metric Learning for Recommendation Shilong Bao Qianqian Xu Zhiyong Yang Yuan He Xiaochun Cao Qingming Huang 53 5 0 02 Sep 2024
DimCL: Dimensional Contrastive Learning For Improving Self-Supervised Learning Thanh Nguyen T. Pham Chaoning Zhang Tung M. Luu Thang Vu Chang D. Yoo 27 9 0 21 Sep 2023
Adaptive Sparse Pairwise Loss for Object Re-Identification Xiao Zhou Yujie Zhong Zhen Cheng Fan Liang Lin Ma 13 39 0 31 Mar 2023
On the Pros and Cons of Momentum Encoder in Self-Supervised Visual Representation Learning T. Pham Chaoning Zhang Axi Niu Kang Zhang Chang D. Yoo 36 11 0 11 Aug 2022
Exploring the Learning Difficulty of Data Theory and Measure Weiyao Zhu Ou Wu Fengguang Su Yingjun Deng 32 5 0 16 May 2022
Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo Chaoning Zhang Kang Zhang T. Pham Axi Niu Zhinan Qiao Chang D. Yoo In So Kweon 24 54 0 30 Mar 2022
Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning ByungSoo Ko Geonmo Gu 85 53 0 05 Mar 2020