Year | Title | Author | Publication | Code | Tasks | Notes | Datasets | Notions |
---|---|---|---|---|---|---|---|---|
2021 | Semi-Supervised Active Learning With Temporal Output Discrepancy | Huang et al. | ICCV | code | Temporal Output Discrepancy | Informative , ResNet-18 ,None , PT+FT , Hard |
Cifar-10, Cifar-100, SVHN, and Caltech-101. | |
2021 | Semi-Supervised Active Learning for Semi-Supervised Models: Exploit Adversarial Examples With Graph-Based Virtual Labels | Guo et al. | ICCV | - | Image Classification | diversity , Graph-based+ResNet , Adversatial ,PT+FT , Hard |
CIFAR- 10 [22] and CIFAR-100 | |
2021 | Influence Selection for Active Learning | Liu et al. | ICCV | - | Image Classification and Object detection | expected gradient , Any Neural Networks , None , Tra , Hard |
CIFAR10, VOC2012, COCO | |
2021 | Contrastive Coding for Active Learning Under Class Distribution Mismatch | Du et al. | ICCV | code | semantic and distinctive , ResNet18 , contrastive learning , PT+FT , Hard |
CIFAR10, CIFAR100, artificial cross-dataset | Class Distribution Mismatch | |
2021 | ReDAL: Region-Based and Diversity-Aware Active Learning for Point Cloud Semantic Segmentation | Wu et al. | ICCV | - | Point Cloud Semantic Segmentation | Diversity , MinkowskiNet/SPVCNN , None , PT+FT , Hard |
S3DIS and Se- manticKITTI datasets | |
2021 | Active Learning for Deep Object Detection via Probabilistic Modeling | Choi et al. | ICCV | code | object detection | epistemic uncertainty , GMM-based , None , PT+FT , Hard |
PASCAL, VOC, MS COCO | |
2021 | Active Learning for Lane Detection: A Knowledge Distillation Approach | Peng et al. | ICCV | - | uncer- tainty and diversity metrics , PointLaneNet/UFLD , Knowledge Distillation , PT+FT , Hard |
CULane [29] and LLAMAS [4] | knowledge distillation approach |