Pinned Repositories
mohan2020
Mohan2020_Moving in the Right Direction; A Regularization for Deep Metric Learning
AutoShape
ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection
class-balanced-loss
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
CreditCardDataAnalysis
Credit Card Data from Kaggle analyzed for CENG574 course of METU CENG department
dd3d
Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
guo2021
Guo2021_Long-Tailed Multi-Label Visual Recognition by Collaborative Training on Uniform and Re-balanced Samplings
LDAM-DRW
[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
MonoDTR
MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer (CVPR 2022)
CENG502-Spring2022
CENG502 Spring 2022 Projects
CENG501-Spring2021
CENG501 Project Repositories
bargul's Repositories
bargul/guo2021
Guo2021_Long-Tailed Multi-Label Visual Recognition by Collaborative Training on Uniform and Re-balanced Samplings
bargul/AutoShape
ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection
bargul/class-balanced-loss
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
bargul/CreditCardDataAnalysis
Credit Card Data from Kaggle analyzed for CENG574 course of METU CENG department
bargul/dd3d
Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
bargul/LDAM-DRW
[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
bargul/MonoDTR
MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer (CVPR 2022)
bargul/ROG
[ICCV 2023] Reconciling Object-Level and Global-Level Objectives for Long-Tail Detection