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20222026
most citedCIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical Researcher

17 citations · 22 across the 8 of their papers we have counts for

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cs.CV2026

SAFIRE: Safety-Critical Benchmark for Fine-grained Fire and Smoke Understanding in Multimodal LLMs

Pengfei Li, Naufal Suryanto, Sicheng Zhang +2

Multimodal Large Language Models (MLLMs) show strong progress on vision-language tasks, yet their reliability in safety-critical settings remains underexplored. Fire-smoke understa…

cs.CV2026

ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP

Sicheng Zhang, Muzammal Naseer, Binzhu Xie +5

CLIP and its variants are widely adopted visual backbones in multimodal systems, but their pretraining remains dominated by descriptive image-text alignment. As downstream applicat…

cs.CV2026

SPARROW: Learning Spatial Precision and Temporal Referential Consistency in Pixel-Grounded Video MLLMs

Mohamad Alansari, Naufal Suryanto, Divya Velayudhan +3

Multimodal large language models (MLLMs) have advanced from image-level reasoning to pixel-level grounding, but extending these capabilities to videos remains challenging as models…

cs.CV2024

Cityscape-Adverse: Benchmarking Robustness of Semantic Segmentation with Realistic Scene Modifications via Diffusion-Based Image Editing

Naufal Suryanto, Andro Aprila Adiputra, Ahmada Yusril Kadiptya +4

Recent advancements in generative AI, particularly diffusion-based image editing, have enabled the transformation of images into highly realistic scenes using only text instruction…

cs.CV2024

Adversarial Manhole: Challenging Monocular Depth Estimation and Semantic Segmentation Models with Patch Attack

Naufal Suryanto, Andro Aprila Adiputra, Ahmada Yusril Kadiptya +2

Monocular depth estimation (MDE) and semantic segmentation (SS) are crucial for the navigation and environmental interpretation of many autonomous driving systems. However, their v…

cs.CV2023

ACTIVE: Towards Highly Transferable 3D Physical Camouflage for Universal and Robust Vehicle Evasion

Naufal Suryanto, Yongsu Kim, Harashta Tatimma Larasati +6

Adversarial camouflage has garnered attention for its ability to attack object detectors from any viewpoint by covering the entire object's surface. However, universality and robus…

cs.CV2022★ 5 cited

DTA: Physical Camouflage Attacks using Differentiable Transformation Network

Naufal Suryanto, Yongsu Kim, Hyoeun Kang +6

To perform adversarial attacks in the physical world, many studies have proposed adversarial camouflage, a method to hide a target object by applying camouflage patterns on 3D obje…