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Loss Functions

123 papers

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Papers

Revisiting AP Loss for Dense Object Detection: Adaptive Ranking Pair Selection CVPR 2022
Balanced MSE for Imbalanced Visual Regression CVPR 2022
A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration CVPR 2022
Geometry-Aware Guided Loss for Deep Crack Recognition CVPR 2022
Towards Robust k-Nearest-Neighbor Machine Translation EMNLP 2022
Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation EMNLP 2022
Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating Attention EMNLP 2022
Calibrating Imbalanced Classifiers with Focal Loss: An Empirical Study EMNLP 2022
Bounds all around: training energy-based models with bidirectional bounds NIPS 2021
$\alpha$-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression NIPS 2021
Searching Parameterized AP Loss for Object Detection NIPS 2021
Learning Modulated Loss for Rotated Object Detection AAAI 2021
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints AAAI 2021
From Label Smoothing to Label Relaxation AAAI 2021
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization AAAI 2021
Learning from Noisy Labels with Complementary Loss Functions AAAI 2021
BERTTune: Fine-Tuning Neural Machine Translation with BERTScore ACL 2021
Style-Aware Normalized Loss for Improving Arbitrary Style Transfer CVPR 2021
Metadata Normalization CVPR 2021
Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection CVPR 2021
Depth Completion With Twin Surface Extrapolation at Occlusion Boundaries CVPR 2021
Generic Perceptual Loss for Modeling Structured Output Dependencies CVPR 2021
Understanding and Simplifying Perceptual Distances CVPR 2021
An Alternative Probabilistic Interpretation of the Huber Loss CVPR 2021
A Sliced Wasserstein Loss for Neural Texture Synthesis CVPR 2021