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Found 7 papers, 2 papers with code
TripletMix: Triplet Data Augmentation for 3D Understanding
Data augmentation has proven to be a vital tool for enhancing the generalization capabilities of deep learning models, especially in the context of 3D vision where traditional datasets are often limited.
SignVTCL: Multi-Modal Continuous Sign Language Recognition Enhanced by Visual-Textual Contrastive Learning
Sign language recognition (SLR) plays a vital role in facilitating communication for the hearing-impaired community.
IFAST: Weakly Supervised Interpretable Face Anti-spoofing from Single-shot Binocular NIR Images
Single-shot face anti-spoofing (FAS) is a key technique for securing face recognition systems, and it requires only static images as input.
DISCO: Distribution-Aware Calibration for Object Detection with Noisy Bounding Boxes
Large-scale well-annotated datasets are of great importance for training an effective object detector.
DPPMask: Masked Image Modeling with Determinantal Point Processes
In particular, we evaluate our method on two representative MIM frameworks, MAE and iBOT.
RepMode: Learning to Re-parameterize Diverse Experts for Subcellular Structure Prediction
In biological research, fluorescence staining is a key technique to reveal the locations and morphology of subcellular structures.
Acknowledging the Unknown for Multi-label Learning with Single Positive Labels
Due to the difficulty of collecting exhaustive multi-label annotations, multi-label datasets often contain partial labels.
