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Found 5 papers, 1 papers with code
BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning
We hope that our efforts could build a solid foundation of backdoor learning to facilitate researchers to investigate existing algorithms, develop more innovative algorithms, and explore the intrinsic mechanism of backdoor learning.
Versatile Backdoor Attack with Visible, Semantic, Sample-Specific, and Compatible Triggers
Deep neural networks (DNNs) can be manipulated to exhibit specific behaviors when exposed to specific trigger patterns, without affecting their performance on benign samples, dubbed \textit{backdoor attack}.
Mutilmodal Feature Extraction and Attention-based Fusion for Emotion Estimation in Videos
The continuous improvement of human-computer interaction technology makes it possible to compute emotions.
StructVPR: Distill Structural Knowledge with Weighting Samples for Visual Place Recognition
In this paper, we propose StructVPR, a novel training architecture for VPR, to enhance structural knowledge in RGB global features and thus improve feature stability in a constantly changing environment.
TransVPR: Transformer-based place recognition with multi-level attention aggregation
In addition, the output tokens from Transformer layers filtered by the fused attention mask are considered as key-patch descriptors, which are used to perform spatial matching to re-rank the candidates retrieved by the global image features.
