115 citations · 165 across the 11 of their papers we have counts for
6 papers · 1 filter
SimpleDG: Simple Domain Generalization Baseline without Bells and Whistles
Zhi Lv, Bo Lin, Siyuan Liang +4
We present a simple domain generalization baseline, which wins second place in both the common context generalization track and the hybrid context generalization track respectively…
Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization
Shichao Dong, Jin Wang, Renhe Ji +3
In this paper, we analyse the generalization ability of binary classifiers for the task of deepfake detection. We find that the stumbling block to their generalization is caused by…
Efficient One Pass Self-distillation with Zipf's Label Smoothing
Jiajun Liang, Linze Li, Zhaodong Bing +4
Self-distillation exploits non-uniform soft supervision from itself during training and improves performance without any runtime cost. However, the overhead during training is ofte…
Explaining Deepfake Detection by Analysing Image Matching
Shichao Dong, Jin Wang, Jiajun Liang +2
This paper aims to interpret how deepfake detection models learn artifact features of images when just supervised by binary labels. To this end, three hypotheses from the perspecti…
Decoupled Knowledge Distillation
Borui Zhao, Quan Cui, Renjie Song +2
State-of-the-art distillation methods are mainly based on distilling deep features from intermediate layers, while the significance of logit distillation is greatly overlooked. To…
Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective
Quan Cui, Bingchen Zhao, Zhao-Min Chen +5
This work simultaneously considers the discriminability and transferability properties of deep representations in the typical supervised learning task, i.e., image classification.…