AVD2: Accident Video Diffusion for Accident Video Description

Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan, ”Real-ESRGAN: Training real-world blind super-resolution with pure synthetic data,” in Proceedings of the IEEE/CVF International Conference on Computer Vision

1914

Earlier work this paper cites.

Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu, ”BLEU: A method for automatic evaluation of machine translation,” in Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics

2002

Earlier work this paper cites.

Chin-Yew Lin and Franz Josef Och, ”Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics,” in Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)

2004

Earlier work this paper cites.

Satanjeev Banerjee and Alon Lavie, ”METEOR: An automatic metric for MT evaluation with improved correlation with human judgments,” in Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization

2005

Earlier work this paper cites.

Dominique Brunet, Edward R Vrscay, and Zhou Wang, ”On the mathematical properties of the structural similarity index,” IEEE Transactions on Image Processing

2011

Earlier work this paper cites.

Jari Korhonen and Junyong You, ”Peak signal-to-noise ratio revisited: Is simple beautiful?” in 2012 Fourth International Workshop on Quality of Multimedia Experience

2012

Earlier work this paper cites.

Subhashini Venugopalan, Marcus Rohrbach, Jeffrey Donahue, Raymond Mooney, Trevor Darrell, and Kate Saenko, ”Sequence to sequence-video to text,” in Proceedings of the IEEE International Conference on Computer Vision

2015

Earlier work this paper cites.

Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh, ”CIDER: Consensus-based image description evaluation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

2015

Earlier work this paper cites.

Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba, ”Generating videos with scene dynamics,” Advances in Neural Information Processing Systems

2016

Earlier work this paper cites.

Alexey Dosovitskiy and Thomas Brox, ”Generating images with perceptual similarity metrics based on deep networks,” Advances in Neural Information Processing Systems

2016

Earlier work this paper cites.

Jinkyu Kim and John Canny, ”Interpretable learning for self-driving cars by visualizing causal attention,” in Proceedings of the IEEE International Conference on Computer Vision

2017

Earlier work this paper cites.

Zaeem Hussain, Mingda Zhang, Xiaozhong Zhang, Keren Ye, Christopher Thomas, Zuha Agha, Nathan Ong, and Adriana Kovashka, ”Automatic understanding of image and video advertisements,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

2017

Earlier work this paper cites.

Steven J Rennie, Etienne Marcheret, Youssef Mroueh, Jerret Ross, and Vaibhava Goel, ”Self-critical sequence training for image captioning,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

2017

Earlier work this paper cites.

A Vaswani, ”Attention is all you need,” Advances in Neural Information Processing Systems

2017

Earlier work this paper cites.

Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter, ”GANs trained by a two time-scale update rule converge to a local Nash equilibrium,” Advances in Neural Information Processing Systems

2017

Earlier work this paper cites.

Jinkyu Kim, Anna Rohrbach, Trevor Darrell, John Canny, and Zeynep Akata, ”Textual explanations for self-driving vehicles,” in Proceedings of the European Conference on Computer Vision (ECCV)

2018

Earlier work this paper cites.

Haoye Cai, Chunyan Bai, Yu-Wing Tai, and Chi-Keung Tang, ”Deep video generation, prediction and completion of human action sequences,” in Proceedings of the European Conference on Computer Vision (ECCV)

2018

Earlier work this paper cites.

Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz, ”Mocogan: Decomposing motion and content for video generation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

2018

Earlier work this paper cites.

Emily Denton and Rob Fergus, ”Stochastic video generation with a learned prior,” in International Conference on Machine Learning

2018

Earlier work this paper cites.

Agrim Gupta, Justin Johnson, Li Fei-Fei, Silvio Savarese, and Alexandre Alahi, ”Social GAN: Socially acceptable trajectories with generative adversarial networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

2018

Earlier work this paper cites.

Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy, ”ESRGAN: Enhanced super-resolution generative adversarial networks,” in Proceedings of the European Conference on Computer Vision (ECCV) Workshops

2018

Earlier work this paper cites.

Ruotian Luo, Brian Price, Scott Cohen, and Gregory Shakhnarovich, ”Discriminability objective for training descriptive captions,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

2018

Earlier work this paper cites.

Alexei Baevski and Michael Auli, ”Adaptive input representations for neural language modeling,” arXiv preprint arXiv:1809.10853

Original

2018

Earlier work this paper cites.

Myle Ott, Sergey Edunov, David Grangier, and Michael Auli, ”Scaling neural machine translation,” arXiv preprint arXiv:1806.00187

Original

2018

Earlier work this paper cites.

Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, and Raquel Urtasun, ”End-to-end interpretable neural motion planner,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

2019

Cited alongside, same era.

Ning Xu, Hanwang Zhang, An-An Liu, Weizhi Nie, Yuting Su, Jie Nie, and Yongdong Zhang, ”Multi-level policy and reward-based deep reinforcement learning framework for image captioning,” IEEE Transactions on Multimedia

2019

Cited alongside, same era.

Thao Minh Le, Vuong Le, Svetha Venkatesh, and Truyen Tran, ”Hierarchical conditional relation networks for video question answering,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

2020

Cited alongside, same era.

Shashank Bujimalla, Mahesh Subedar, and Omesh Tickoo, ”B-SCST: Bayesian self-critical sequence training for image captioning,” arXiv preprint arXiv:2004.02435

Original

2020

Cited alongside, same era.

Chongqi Zhang, Ziwen Zhang, Yao Deng, Yueyi Zhang, Mingzhe Chong, Yunhua Tan, and Pukun Liu, ”Blind super-resolution for SAR images with speckle noise based on deep learning probabilistic degradation model and SAR priors,” Remote Sensing

2023

Later among the works it cites.

Lijun Yu, José Lezama, Nitesh B Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Vighnesh Birodkar, Agrim Gupta, Xiuye Gu, and others, ”Language Model Beats Diffusion–Tokenizer is Key to Visual Generation,” arXiv preprint arXiv:2310.05737

Original

2023

Later among the works it cites.

Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, and Hongyang Li, ”End-to-end autonomous driving: Challenges and frontiers,” IEEE Transactions on Pattern Analysis and Machine Intelligence

2024

Later among the works it cites.

Ana-Maria Marcu, Long Chen, Jan Hünermann, Alice Karnsund, Benoit Hanotte, Prajwal Chidananda, Saurabh Nair, Vijay Badrinarayanan, Alex Kendall, Jamie Shotton, and others, ”Lingoqa: Visual question answering for autonomous driving,” in European Conference on Computer Vision