Traffic Sign Recognition

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

10 leaderboard tables shown for this task, 10 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

7 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 43 papers with code (127 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Architecturing Binarized Neural Networks for Traffic Sign Recognition
  27 Mar 2023 4 repositories listed
  Traffic signs support road safety and managing the flow of traffic, hence are an integral part of any vision system for autonomous driving.
• Novel Deep Learning Model for Traffic Sign Detection Using Capsule Networks
  11 May 2018 3 repositories listed
  Convolutional neural networks are the most widely used deep learning algorithms for traffic signal classification till date but they fail to capture pose, view, orientation of the images because of the intrinsic…
• Targeted Physical-World Attention Attack on Deep Learning Models in Road Sign Recognition
  9 Oct 2020 2 repositories listed
  To alleviate these problems, this paper proposes the targeted attention attack (TAA) method for real world road sign attack.
• Traffic Sign Detection under Challenging Conditions: A Deeper Look Into Performance Variations and Spectral Characteristics
  29 Aug 2019 2 repositories listed
  We investigate the effect of challenging conditions through spectral analysis and show that challenging conditions can lead to distinct magnitude spectrum characteristics.
• A Hierarchical Deep Architecture and Mini-Batch Selection Method For Joint Traffic Sign and Light Detection
  20 Jun 2018 2 repositories listed
  The root cause of this issue is that no public dataset contains both traffic light and sign labels, which leads to difficulties in developing a joint detection framework.
• Traffic Sign Classification Using Deep Inception Based Convolutional Networks
  10 Nov 2015 2 repositories listed
  In this work, we propose a novel deep network for traffic sign classification that achieves outstanding performance on GTSRB surpassing all previous methods.
• Evaluating Adversarial Attacks on Traffic Sign Classifiers beyond Standard Baselines
  12 Dec 2024 1 repository listed
  Adversarial attacks on traffic sign classification models were among the first successfully tried in the real world.
• CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense
  30 Oct 2024 1 repository listed Syntology ran 3 of 17 samples · 14 unverified
  Despite ongoing efforts to defend neural classifiers from adversarial attacks, they remain vulnerable, especially to unseen attacks.
• TSCLIP: Robust CLIP Fine-Tuning for Worldwide Cross-Regional Traffic Sign Recognition
  23 Sep 2024 1 repository listed
  In this paper, we propose TSCLIP, a robust fine-tuning approach with the contrastive language-image pre-training (CLIP) model for worldwide cross-regional traffic sign recognition.
• SeqNet: Sequential Networks for One-Shot Traffic Sign Recognition With Transfer Learning
  23 Sep 2024 1 repository listed
  One-shot object recognition is a challenging task for deep neural networks in which a deep model classifies query examples based on support images.
• Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade Defense
  1 Oct 2023 1 repository listed Syntology ran 15 of 22 samples · 7 unverified · 7 pointer-only (licence)
  In VCB attacks, any sample from a class activates the implanted backdoor when the secret trigger is present.
• Benchmarking Local Robustness of High-Accuracy Binary Neural Networks for Enhanced Traffic Sign Recognition
  25 Sep 2023 1 repository listed
  The results of the 4th International Verification of Neural Networks Competition (VNN-COMP'23) revealed the fact that 4, out of 7, solvers can handle many of our benchmarks randomly selected (minimum is 6, maximum is…
• Adversarial Robustness Certification for Bayesian Neural Networks
  23 Jun 2023 1 repository listed
  We study the problem of certifying the robustness of Bayesian neural networks (BNNs) to adversarial input perturbations.
• Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous driving
  3 May 2023 1 repository listed
  The dataset is composed of Frames, Sequences, and Drives, designed to encompass both data diversity and support for spatio-temporal learning, sensor fusion, localization, and mapping.
• Traffic Sign Recognition Dataset and Data Augmentation
  31 Mar 2023 1 repository listed
  Although there are many datasets for traffic sign classification, there are few datasets collected for traffic sign recognition and few of them obtain enough instances especially for training a model with the deep…
• Robust Transformer with Locality Inductive Bias and Feature Normalization
  27 Jan 2023 1 repository listed
  In this paper, we explore the robustness of vision transformers against adversarial perturbations and try to enhance their robustness/accuracy trade-off in white box attack settings.
• Simultaneously Optimizing Perturbations and Positions for Black-box Adversarial Patch Attacks
  26 Dec 2022 1 repository listed
  Extensive experiments are conducted on the Face Recognition (FR) task, and results on four representative FR models show that our method can significantly improve the attack success rate and query efficiency.
• GLARE: A Dataset for Traffic Sign Detection in Sun Glare
  19 Sep 2022 1 repository listed
  It provides an essential enrichment to the widely used LISA Traffic Sign dataset.
• Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring
  11 Jul 2022 1 repository listed
  Limitations in setting SafeML up properly include the lack of a systematic approach for determining, for a given application, how many operational samples are needed to yield reliable distance information as well as to…
• Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon
  8 Mar 2022 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  A new type of non-invasive attacks emerged recently, which attempt to cast perturbation onto the target by optics based tools, such as laser beam and projector.
• Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
  16 Feb 2022 1 repository listed
  Discriminative self-supervised learning allows training models on any random group of internet images, and possibly recover salient information that helps differentiate between the images.
• Improving traffic sign recognition by active search
  29 Nov 2021 1 repository listed
  We demonstrate that by sorting the samples of a large, unlabeled set by the estimated probability of belonging to the rare class, we can efficiently identify samples from the rare class.
• A real-time and high-precision method for small traffic-signs recognition
  25 Sep 2021 1 repository listed
  However, in real applications, small traffic-signs recognition is still challenging.
• Toward Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems
  3 Aug 2021 1 repository listed
  The application of artificial intelligence (AI) and data-driven decision-making systems in autonomous vehicles is growing rapidly.
• Adversarial Sticker: A Stealthy Attack Method in the Physical World
  14 Apr 2021 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  Unlike the previous adversarial patches by designing perturbations, our method manipulates the sticker's pasting position and rotation angle on the objects to perform physical attacks.
• Sill-Net: Feature Augmentation with Separated Illumination Representation
  6 Feb 2021 1 repository listed
  For visual object recognition tasks, the illumination variations can cause distinct changes in object appearance and thus confuse the deep neural network based recognition models.
• SLAP: Improving Physical Adversarial Examples with Short-Lived Adversarial Perturbations
  8 Jul 2020 1 repository listed
  Research into adversarial examples (AE) has developed rapidly, yet static adversarial patches are still the main technique for conducting attacks in the real world, despite being obvious, semi-permanent and unmodifiable…
• Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment
  23 Jun 2020 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  To solve this problem, we introduce a Gaussian-guided latent alignment approach to align the latent feature distributions of the two domains under the guidance of the prior distribution.
• Towards Context-Agnostic Learning Using Synthetic Data
  29 May 2020 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  We propose a novel setting for learning, where the input domain is the image of a map defined on the product of two sets, one of which completely determines the labels.
• NetTailor: Tuning the Architecture, Not Just the Weights
  29 Jun 2019 1 repository listed
  Under the standard paradigm of network fine-tuning, an entirely new CNN is learned per task, and the final network size is independent of task complexity.

Syntology lines on 6 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.