Real-IAD-MVN supplies multi-view normal vector data and a reconstruction baseline that outperforms prior multimodal methods for geometric industrial anomaly detection.
Real-iad: A real-world multi-view dataset for benchmarking versatile industrial anomaly detec- tion
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UniSpector organizes visual prompt space with spatial-spectral and contrastive encoders to support open-set defect localization, beating baselines by at least 19.7% AP50b and 15.8% AP50m on the new Inspect Anything benchmark.
ViSurf unifies SFT and RLVR for LVLMs in one training stage by injecting ground-truth labels into rollouts and applying novel reward controls, outperforming standalone and two-stage baselines on diverse benchmarks.
citing papers explorer
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Real-IAD MVN: A Multi-View Normal Vector Dataset and Benchmark for High-Fidelity Industrial Anomaly Detection
Real-IAD-MVN supplies multi-view normal vector data and a reconstruction baseline that outperforms prior multimodal methods for geometric industrial anomaly detection.
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UniSpector: Towards Universal Open-set Defect Recognition via Spectral-Contrastive Visual Prompting
UniSpector organizes visual prompt space with spatial-spectral and contrastive encoders to support open-set defect localization, beating baselines by at least 19.7% AP50b and 15.8% AP50m on the new Inspect Anything benchmark.
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ViSurf: Visual Supervised-and-Reinforcement Fine-Tuning for Large Vision-and-Language Models
ViSurf unifies SFT and RLVR for LVLMs in one training stage by injecting ground-truth labels into rollouts and applying novel reward controls, outperforming standalone and two-stage baselines on diverse benchmarks.