mlsanityData to 7 Oct 2026

ECCV 2024 W-CODA: 1st Workshop on Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving

arXiv 2507.01735 ↗First posted 2 Jul 2025cs.CV cs.AI cs.CLcited by 5

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Abstract (arXiv)

In this paper, we present details of the 1st W-CODA workshop, held in conjunction with the ECCV 2024. W-CODA aims to explore next-generation solutions for autonomous driving corner cases, empowered by state-of-the-art multimodal perception and comprehension techniques. 5 Speakers from both academia and industry are invited to share their latest progress and opinions. We collect research papers and hold a dual-track challenge, including both corner case scene understanding and generation. As the pioneering effort, we will continuously bridge the gap between frontier autonomous driving techniques and fully intelligent, reliable self-driving agents robust towards corner cases.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 23 of its 29 references that are in the map. First posted on arXiv 2 Jul 2025.

Builds on

23 of 29 references.

References · 23

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
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  11. 2024Automated Evaluation of Large Vision-Language Models on Self-driving Corner Casescited by 75
  12. 2024MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenescited by 70
11 more
  1. 2024EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotionscited by 44
  2. 2021MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Drivingcited by 41
  3. 2023Mixed Autoencoder for Self-supervised Visual Representation Learningcited by 38
  4. 2023Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysiscited by 34
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  6. 2021Corner Cases for Visual Perception in Automated Driving: Some Guidance on Detection Approachescited by 27
  7. 2022Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routingcited by 18
  8. 2024Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Expertscited by 16
  9. 2024Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignmentcited by 10
  10. 2024Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Modelscited by 7
  11. 2025Reasoning-Aligned Perception Decoupling for Scalable Multi-modal Reasoningcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2025GenieDrive: Towards Physics-Aware Driving World Model with 4D Occupancy Guided Video Generationcited by 10
  2. 2026Composing Driving Worlds through Disentangled Control for Adversarial Scenario Generationcited by 2
  3. 2026DriveJudge: Rethinking Autonomous Driving Evaluation with Vision-Language Modelscited by 2
  4. 2026VistaGEN: Consistent Driving Video Generation with Fine-Grained Control Using Multiview Visual-Language Reasoningcited by 0
  5. 2026AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyondcited by 0