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Realistic and controllable traffic simulation is a core capability that is necessary to accelerate autonomous vehicle (AV) development. However, current approaches for controlling learning-based traffic models require significant domain…

Robotics · Computer Science 2023-10-20 Ziyuan Zhong , Davis Rempe , Yuxiao Chen , Boris Ivanovic , Yulong Cao , Danfei Xu , Marco Pavone , Baishakhi Ray

The creation of complex 3D scenes tailored to user specifications has been a tedious and challenging task with traditional 3D modeling tools. Although some pioneering methods have achieved automatic text-to-3D generation, they are generally…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Xiuyu Yang , Yunze Man , Jun-Kun Chen , Yu-Xiong Wang

Recent advances in scene-based video generation enable coherent visual narratives from structured prompts, yet a key aspect of storytelling -- character-driven dialogue and speech -- remains underexplored. We present a modular pipeline that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Taewon Kang , Ming C. Lin

We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning. Specifically, we consider the problems of training a perception system to handle rare events,…

Camera-controllable video generation aims to synthesize videos with flexible and physically plausible camera movements. However, existing methods either provide imprecise camera control from text prompts or rely on labor-intensive manual…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Haoyu Zhao , Zihao Zhang , Jiaxi Gu , Haoran Chen , Qingping Zheng , Pin Tang , Yeyin Jin , Yuang Zhang , Junqi Cheng , Zenghui Lu , Peng Shu , Zuxuan Wu , Yu-Gang Jiang

Existing video-language models can generate factual descriptions of road events but lack control over how these events are expressed: their tone, urgency, or style. This limits deployment in communication-critical settings where the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Chirag Parikh , Siddhi Pravin Lipare , Ravi Kiran Sarvadevabhatla

Reliable anticipation of traffic accidents is essential for advancing autonomous driving systems. However, this objective is limited by two fundamental challenges: the scarcity of diverse, high-quality training data and the frequent absence…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Yanchen Guan , Haicheng Liao , Chengyue Wang , Xingcheng Liu , Jiaxun Zhang , Zhenning Li

Camera control, which achieves diverse visual effects by changing camera position and pose, has attracted widespread attention. However, existing methods face challenges such as complex interaction and limited control capabilities. To…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Xiaoda Yang , Jiayang Xu , Kaixuan Luan , Xinyu Zhan , Hongshun Qiu , Shijun Shi , Hao Li , Shuai Yang , Li Zhang , Checheng Yu , Cewu Lu , Lixin Yang

Verifying highly automated driving functions can be challenging, requiring identifying relevant test scenarios. Scenario-based testing will likely play a significant role in verifying these systems, predominantly occurring within…

Robotics · Computer Science 2024-04-29 Maximilian Zipfl , Barbara Schütt , J. Marius Zöllner

With the growing adoption of vision-language-action models and world models in autonomous driving systems, scalable image tokenization becomes crucial as the interface for the visual modality. However, most existing tokenizers are designed…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Dong Zhuo , Wenzhao Zheng , Sicheng Zuo , Siming Yan , Lu Hou , Jie Zhou , Jiwen Lu

Until recently, the general corpus of CLIP-type fundamental models has widely explored either the retrieval of short descriptions or the classification of objects in the scene as SINGLE-object image classification task. The same holds for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Advik Sinha , Saurabh Atreya , Aashutosh A , Sk Aziz Ali , Abhijit Das

Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and index scenarios, various vehicle…

Software Engineering · Computer Science 2024-05-15 Cheng Chang , Jiawei Zhang , Jingwei Ge , Zuo Zhang , Junqing Wei , Li Li , Fei-Yue Wang

For autonomous vehicles, safe navigation in complex environments depends on handling a broad range of diverse and rare driving scenarios. Simulation- and scenario-based testing have emerged as key approaches to development and validation of…

Autonomous Vehicles (AV)'s wide-scale deployment appears imminent despite many safety challenges yet to be resolved. The modern autonomous vehicles will undoubtedly include machine learning and probabilistic techniques that add significant…

Robotics · Computer Science 2022-03-16 Dhanoop Karunakaran , Julie Stephany Berrio , Stewart Worrall , Eduardo Nebot

Generating immersive 3D scenes from texts is a core task in computer vision, crucial for applications in virtual reality and game development. Despite the promise of leveraging 2D diffusion priors, existing methods suffer from spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Jisheng Chu , Wenrui Li , Rui Zhao , Wangmeng Zuo , Shifeng Chen , Xiaopeng Fan

Testing and validating Autonomous Vehicle (AV) performance in safety-critical and diverse scenarios is crucial before real-world deployment. However, manually creating such scenarios in simulation remains a significant and time-consuming…

Robotics · Computer Science 2025-09-29 Efimia Panagiotaki , Georgi Pramatarov , Lars Kunze , Daniele De Martini

We propose a weakly-supervised approach for conditional image generation of complex scenes where a user has fine control over objects appearing in the scene. We exploit sparse semantic maps to control object shapes and classes, as well as…

Computer Vision and Pattern Recognition · Computer Science 2020-11-23 Dario Pavllo , Aurelien Lucchi , Thomas Hofmann

In this paper, we consider a novel and practical case for talking face video generation. Specifically, we focus on the scenarios involving multi-people interactions, where the talking context, such as audience or surroundings, is present.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-29 Meidai Xuanyuan , Yuwang Wang , Honglei Guo , Qionghai Dai

Despite recent advancements in single-domain or single-object image generation, it is still challenging to generate complex scenes containing diverse, multiple objects and their interactions. Scene graphs, composed of nodes as objects and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-13 Sarthak Garg , Helisa Dhamo , Azade Farshad , Sabrina Musatian , Nassir Navab , Federico Tombari

Text-to-3D scene generation from natural language is highly desirable for digital content creation. However, existing methods are largely domain-restricted or reliant on predefined spatial relationships, limiting their capacity for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Jun Luo , Jiaxiang Tang , Ruijie Lu , Gang Zeng