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Found 5 papers, 2 papers with code
RLSAC: Reinforcement Learning enhanced Sample Consensus for End-to-End Robust Estimation
Therefore, RLSAC can avoid differentiating to learn the features and the feedback of downstream tasks for end-to-end robust estimation.
ABC: Attention with Bilinear Correlation for Infrared Small Target Detection
Infrared small target detection (ISTD) has a wide range of applications in early warning, rescue, and guidance.
TaCo: Textual Attribute Recognition via Contrastive Learning
To realize this goal, we design the learning paradigm from three perspectives: 1) generating attribute views, 2) extracting subtle but crucial details, and 3) exploiting valued view pairs for learning, to fully unlock the pre-training potential.
STN: Scalable Tensorizing Networks via Structure-Aware Training and Adaptive Compression
Deep neural networks (DNNs) have delivered a remarkable performance in many tasks of computer vision.
Multi-Tensor Network Representation for High-Order Tensor Completion
In particular, each component can be represented as multilinear connections over several latent factors and naturally mapped to a specific tensor network (TN) topology.
