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Found 6 papers, 1 papers with code
A Self-supervised Joint Training Framework for Document Reranking
Pretrained language models such as BERT have been successfully applied to a wide range of natural language processing tasks and also achieved impressive performance in document reranking tasks.
Event Voxel Set Transformer for Spatiotemporal Representation Learning on Event Streams
To fit the sparse nature of events and sufficiently explore the relationship between them, we develop a novel attention-aware model named Event Voxel Set Transformer (EVSTr) for spatiotemporal representation learning on event streams.
A Dynamic Graph CNN with Cross-Representation Distillation for Event-Based Recognition
Recent advances in event-based research prioritize sparsity and temporal precision.
TokenHPE: Learning Orientation Tokens for Efficient Head Pose Estimation via Transformers
To leverage the observed findings, we propose a novel critical minority relationship-aware method based on the Transformer architecture in which the facial part relationships can be learned.
TransIFC: Invariant Cues-aware Feature Concentration Learning for Efficient Fine-grained Bird Image Classification
To this end, two novel modules are proposed to leverage the characteristics of bird images, namely, the hierarchy stage feature aggregation (HSFA) module and the feature in feature abstraction (FFA) module.
Ranked #7 on
Fine-Grained Image Classification
on NABirds
A Voxel Graph CNN for Object Classification with Event Cameras
This study aims to address the core problem of balancing accuracy and model complexity for event-based classification models.
