{"total":30,"rows":[{"id":"2106.03805","title":"3DB: A Framework for Debugging Computer Vision Models","created":"2021-06-07","cited_by_count":31,"area":null},{"id":"2112.09151","title":"TAFIM: Targeted Adversarial Attacks against Facial Image Manipulations","created":"2021-12-16","cited_by_count":26,"area":null},{"id":"2206.07179","title":"Proximal Splitting Adversarial Attacks for Semantic Segmentation","created":"2022-06-14","cited_by_count":23,"area":null},{"id":"2212.01806","title":"Recognizing Object by Components with Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural Networks","created":"2022-12-04","cited_by_count":18,"area":null},{"id":"2405.01636","title":"Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey","created":"2024-05-02","cited_by_count":11,"area":null},{"id":"2103.05232","title":"Stabilized Medical Image Attacks","created":"2021-03-09","cited_by_count":10,"area":null},{"id":"2107.01943","title":"When and How to Fool Explainable Models (and Humans) with Adversarial Examples","created":"2021-07-05","cited_by_count":10,"area":null},{"id":"2312.02207","title":"TranSegPGD: Improving Transferability of Adversarial Examples on Semantic Segmentation","created":"2023-12-03","cited_by_count":10,"area":null},{"id":"2107.04401","title":"Improving Model Robustness with Latent Distribution Locally and Globally","created":"2021-07-08","cited_by_count":9,"area":null},{"id":"2404.08255","title":"Practical Region-level Attack against Segment Anything Models","created":"2024-04-12","cited_by_count":9,"area":null},{"id":"2105.00113","title":"IPatch: A Remote Adversarial Patch","created":"2021-04-30","cited_by_count":7,"area":null},{"id":"2202.01186","title":"Smoothed Embeddings for Certified Few-Shot Learning","created":"2022-02-02","cited_by_count":6,"area":null},{"id":"2102.00798","title":"Landmark Breaker: Obstructing DeepFake By Disturbing Landmark Extraction","created":"2021-02-01","cited_by_count":5,"area":null},{"id":"2303.12054","title":"Influencer Backdoor Attack on Semantic Segmentation","created":"2023-03-21","cited_by_count":5,"area":null},{"id":"2304.02693","title":"A Certified Radius-Guided Attack Framework to Image Segmentation Models","created":"2023-04-05","cited_by_count":5,"area":null},{"id":"2308.07673","title":"A Review of Adversarial Attacks in Computer Vision","created":"2023-08-15","cited_by_count":5,"area":null},{"id":"2408.09839","title":"Segment-Anything Models Achieve Zero-shot Robustness in Autonomous Driving","created":"2024-08-19","cited_by_count":5,"area":null},{"id":"2111.08485","title":"Consistent Semantic Attacks on Optical Flow","created":"2021-11-16","cited_by_count":4,"area":null},{"id":"2307.16572","title":"Transferable Attack for Semantic Segmentation","created":"2023-07-31","cited_by_count":4,"area":null},{"id":"2210.13289","title":"Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses","created":"2022-10-24","cited_by_count":3,"area":null},{"id":"2104.00139","title":"Adversarial Heart Attack: Neural Networks Fooled to Segment Heart Symbols in Chest X-Ray Images","created":"2021-03-31","cited_by_count":1,"area":null},{"id":"2111.08954","title":"Tracklet-Switch Adversarial Attack against Pedestrian Multi-Object Tracking Trackers","created":"2021-11-17","cited_by_count":1,"area":null},{"id":"2208.07174","title":"A Human-in-the-Middle Attack against Object Detection Systems","created":"2022-08-15","cited_by_count":1,"area":null},{"id":"2306.14217","title":"On Evaluating the Adversarial Robustness of Semantic Segmentation Models","created":"2023-06-25","cited_by_count":1,"area":null},{"id":"2401.09624","title":"MITS-GAN: Safeguarding Medical Imaging from Tampering with Generative Adversarial Networks","created":"2024-01-17","cited_by_count":1,"area":null},{"id":"2402.01220","title":"Delving into Decision-based Black-box Attacks on Semantic Segmentation","created":"2024-02-02","cited_by_count":1,"area":null},{"id":"2407.09150","title":"Evaluating the Adversarial Robustness of Semantic Segmentation: Trying Harder Pays Off","created":"2024-07-12","cited_by_count":1,"area":null},{"id":"2105.03669","title":"Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs","created":"2021-05-08","cited_by_count":0,"area":null},{"id":"2110.06164","title":"M2GAN: A Multi-Stage Self-Attention Network for Image Rain Removal on Autonomous Vehicles","created":"2021-10-12","cited_by_count":0,"area":null},{"id":"2111.01093","title":"Correlation between image quality metrics of magnetic resonance images and the neural network segmentation accuracy","created":"2021-11-01","cited_by_count":0,"area":null}],"next_cursor":null}