{"total":34,"rows":[{"id":"2110.11328","title":"A Fine-Grained Analysis on Distribution Shift","created":"2021-10-21","cited_by_count":171,"area":null},{"id":"2104.03066","title":"Distributional Robustness Loss for Long-tail Learning","created":"2021-04-07","cited_by_count":84,"area":null},{"id":"2105.03494","title":"The iWildCam 2021 Competition Dataset","created":"2021-05-07","cited_by_count":77,"area":null},{"id":"2306.03536","title":"On Pitfalls of Test-Time Adaptation","created":"2023-06-06","cited_by_count":64,"area":null},{"id":"2112.04764","title":"3D-VField: Adversarial Augmentation of Point Clouds for Domain Generalization in 3D Object Detection","created":"2021-12-09","cited_by_count":43,"area":null},{"id":"2103.00560","title":"Perspectives on individual animal identification from biology and computer vision","created":"2021-02-28","cited_by_count":31,"area":null},{"id":"2302.11861","title":"Out-of-Domain Robustness via Targeted Augmentations","created":"2023-02-23","cited_by_count":24,"area":null},{"id":"2106.04569","title":"Simulated Adversarial Testing of Face Recognition Models","created":"2021-06-08","cited_by_count":10,"area":null},{"id":"2209.05407","title":"Segmenting Known Objects and Unseen Unknowns without Prior Knowledge","created":"2022-09-12","cited_by_count":9,"area":null},{"id":"2307.10586","title":"A Holistic Assessment of the Reliability of Machine Learning Systems","created":"2023-07-20","cited_by_count":9,"area":null},{"id":"2106.15083","title":"ElephantBook: A Semi-Automated Human-in-the-Loop System for Elephant Re-Identification","created":"2021-06-29","cited_by_count":8,"area":null},{"id":"2310.19247","title":"Uncertainty-guided Boundary Learning for Imbalanced Social Event Detection","created":"2023-10-30","cited_by_count":8,"area":null},{"id":"2202.02283","title":"Choosing an Appropriate Platform and Workflow for Processing Camera Trap Data using Artificial Intelligence","created":"2022-02-04","cited_by_count":6,"area":null},{"id":"2211.16499","title":"Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing","created":"2022-11-29","cited_by_count":6,"area":null},{"id":"2106.15681","title":"SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems","created":"2021-06-29","cited_by_count":4,"area":null},{"id":"2308.15479","title":"3D Adversarial Augmentations for Robust Out-of-Domain Predictions","created":"2023-08-29","cited_by_count":4,"area":null},{"id":"2110.12216","title":"Domain Adaptation for Rare Classes Augmented with Synthetic Samples","created":"2021-10-23","cited_by_count":3,"area":null},{"id":"2210.05667","title":"Human Body Measurement Estimation with Adversarial Augmentation","created":"2022-10-11","cited_by_count":3,"area":null},{"id":"2112.05134","title":"A Shared Representation for Photorealistic Driving Simulators","created":"2021-12-09","cited_by_count":2,"area":null},{"id":"2407.18428","title":"Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift","created":"2024-07-25","cited_by_count":2,"area":null},{"id":"2408.10831","title":"ZebraPose: Zebra Detection and Pose Estimation using only Synthetic Data","created":"2024-08-20","cited_by_count":2,"area":null},{"id":"2511.11882","title":"Lacking Data? No worries! How synthetic images can alleviate image scarcity in wildlife surveys: a case study with muskox (Ovibos moschatus)","created":"2025-11-14","cited_by_count":2,"area":null},{"id":"2106.12212","title":"Image-to-Image Translation of Synthetic Samples for Rare Classes","created":"2021-06-23","cited_by_count":1,"area":null},{"id":"2306.13803","title":"Elephants and Algorithms: A Review of the Current and Future Role of AI in Elephant Monitoring","created":"2023-06-23","cited_by_count":1,"area":null},{"id":"2402.09786","title":"Examining Pathological Bias in a Generative Adversarial Network Discriminator: A Case Study on a StyleGAN3 Model","created":"2024-02-15","cited_by_count":1,"area":null},{"id":"2412.00290","title":"Adapting the re-ID challenge for static sensors","created":"2024-11-30","cited_by_count":1,"area":null},{"id":"2508.09550","title":"Exploring the Equivalence of Closed-Set Generative and Real Data Augmentation in Image Classification","created":"2025-08-13","cited_by_count":1,"area":null},{"id":"2603.04163","title":"Degradation-based augmented training for robust individual animal re-identification","created":"2026-03-04","cited_by_count":1,"area":null},{"id":"2603.26754","title":"Generating Synthetic Wildlife Health Data from Camera Trap Imagery: A Pipeline for Alopecia and Body Condition Training Data","created":"2026-03-23","cited_by_count":1,"area":null},{"id":"2303.01003","title":"Target Domain Data induces Negative Transfer in Mixed Domain Training with Disjoint Classes","created":"2023-03-02","cited_by_count":0,"area":null},{"id":"2405.11112","title":"Enhancing Understanding Through Wildlife Re-Identification","created":"2024-05-17","cited_by_count":0,"area":null},{"id":"2405.15240","title":"Towards Real-world Debiasing: Rethinking Evaluation, Challenge, and Solution","created":"2024-05-24","cited_by_count":0,"area":null},{"id":"2409.18611","title":"Differentially Private Non Parametric Copulas: Generating synthetic data with non parametric copulas under privacy guarantees","created":"2024-09-27","cited_by_count":0,"area":null},{"id":"2509.04959","title":"On the Normalization of Confusion Matrices: Methods and Geometric Interpretations","created":"2025-09-05","cited_by_count":0,"area":null}],"next_cursor":null}