{"total":13,"items":[{"citing_arxiv_id":"2607.00802","ref_index":31,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"CellPrior-Net: Prior-Guided Nuclei Detection and Classification for H&E Whole-Slide Images","primary_cat":"cs.MM","submitted_at":"2026-07-01T11:31:09+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":4.0,"formal_verification":"none","one_line_summary":"CellPrior-Net integrates hematoxylin channel prior into a lightweight CNN for nuclei detection and classification in H&E WSIs, claiming comparable accuracy to SOTA with significantly reduced inference time across 10.4M nuclei from diverse datasets.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.19961","ref_index":1,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"Addressing Detail Bottlenecks in Latent Diffusion for RGB-to-SWIR Image Translation","primary_cat":"cs.CV","submitted_at":"2026-06-18T08:59:03+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Introduces SCAE with skip connections and LGE to fix detail loss in LDMs for RGB-to-SWIR translation, yielding up to 2x mAP gains and 3.4x on small objects while reaching SOTA FID.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.18058","ref_index":68,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"Multiscale reconstruction of protein conformations from cryo-EM images","primary_cat":"eess.IV","submitted_at":"2026-06-16T15:35:31+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"A multiscale optimization method using explicit protein backbone geometry reconstructs atomic models from cryo-EM data, showing improved RMSD and TM scores on three simulated datasets.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.24621","ref_index":2,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"Phase-Aware Wavelet-Based-Scattering Encoder-Decoder for Dense Predictions","primary_cat":"cs.CV","submitted_at":"2026-05-23T15:12:43+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"A phase-aware wavelet scattering encoder-decoder improves denoising PSNR by preserving phase in skip connections, with reported gains of +2.17 dB from breaking translation invariance and +1.03 dB from phase preservation.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.17347","ref_index":1,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"Position: Age Estimation Models Do Not Process Biometric Data","primary_cat":"cs.CY","submitted_at":"2026-05-17T09:37:28+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"Empirical evaluation shows age estimation models perform orders of magnitude below identification thresholds on face verification benchmarks, indicating they do not extract identity-discriminative representations.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.12608","ref_index":34,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"A Data Efficiency Study of Synthetic Fog for Object Detection Using the Clear2Fog Pipeline","primary_cat":"cs.CV","submitted_at":"2026-05-12T18:01:00+00:00","verdict":null,"verdict_confidence":null,"novelty_score":null,"formal_verification":null,"one_line_summary":null,"context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.23799","ref_index":34,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"VitaminP: cross-modal learning enables whole-cell segmentation from routine histology","primary_cat":"cs.CV","submitted_at":"2026-04-26T16:43:37+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"VitaminP uses paired H&E-mIF data to train a model that transfers molecular boundary information, enabling accurate whole-cell segmentation directly from routine H&E histology across 34 cancer types.","context_count":1,"top_context_role":"background","top_context_polarity":"unclear","context_text":"url: https://ieeexplore.ieee.org/document/9607772/ (visited on 02/22/2026). [33] Neeraj Kumar et al. \"A Multi-Organ Nucleus Segmentation Challenge\". In:IEEE Transactions on Medical Imaging39.5 (May 2020), pp. 1380-1391.issn: 0278-0062, 1558-254X.doi: 10.1109/ TMI.2019.2947628 .url: https://ieeexplore.ieee.org/document/8880654/ (visited on 02/22/2026). [34] Peter Naylor et al. \"Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map\". In:IEEE Transactions on Medical Imaging38.2 (Feb. 2019), pp. 448-459.issn: 0278-0062, 1558-254X.doi: 10.1109/TMI.2018.2865709 .url: https://ieeexplore.ieee. org/document/8438559/(visited on 01/21/2026). [35] Amirreza Mahbod et al. \"CryoNuSeg: A dataset for nuclei instance segmentation of cryosectioned H&E-"},{"citing_arxiv_id":"2604.21801","ref_index":22,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"SyMTRS: Benchmark Multi-Task Synthetic Dataset for Depth, Domain Adaptation and Super-Resolution in Aerial Imagery","primary_cat":"cs.CV","submitted_at":"2026-04-23T15:59:12+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"A new large-scale synthetic multi-task benchmark dataset supplying pixel-perfect depth, domain-shifted night imagery, and multi-scale low-resolution pairs for aerial remote sensing.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.14849","ref_index":2,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"Efficient Search of Implantable Adaptive Cells for Medical Image Segmentation","primary_cat":"cs.CV","submitted_at":"2026-04-16T10:34:57+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"IAC-LTH accelerates IAC search for medical segmentation by progressively pruning unstable operations via Jensen-Shannon divergence on per-edge importance distributions, delivering comparable patient-level Dice scores with substantially lower wall-clock cost.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.03117","ref_index":15,"ref_count":1,"confidence":0.9,"is_internal_anchor":false,"paper_title":"Revealing Physical-World Semantic Vulnerabilities: Universal Adversarial Patches for Infrared Vision-Language Models","primary_cat":"cs.CV","submitted_at":"2026-04-03T15:42:55+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"UCGP is a universal physical adversarial patch that compromises cross-modal semantic alignment in IR-VLMs through curved-grid parameterization and representation-space disruption.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"Sustainability, 14(18):11161, 2022. doi: 10.3390/su141811161. [14] Xinyu Jia, Chuang Zhu, Minzhen Li, Wenqi Tang, and Wenli Zhou. Llvip: A visible-infrared paired dataset for low-light vision. InProceedings of the IEEE/CVF International Conference on Computer Vision Workshops, pages 3489-3497, Montreal, QC, Canada, 2021. IEEE. doi: 10.1109/ICCVW54120.2021.00389. [15] Wanqi Zhou, Shuanghao Bai, Danilo P. Mandic, Qibin Zhao, and Badong Chen. Revisiting the adversarial ro- bustness of vision language models: a multimodal per- spective. arXiv preprint arXiv:2404.19287, 2024. URL https://arxiv.org/abs/2404.19287. [16] IanJ.Goodfellow,JonathonShlens,andChristianSzegedy. 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