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21st Pacific Rim International Conference on artificial intelligence, PRICAI 2024

作者： Zhao, Jiayu Wei, Fei-Fei Liang, Anqi Mei, Kuizhi College of Artificial Intelligence Xi’an Jiaotong University Xi’an China National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center of Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China

ISBN: (纸本)9789819601219

This paper introduces BFVTModel, an efficient 3D semantic segmentation Model. Multi-modal segmentators, which employ LiDAR and Camera sensors as input, have gained popularity owing to their capacity to leverage the semantic information in image data and complementary details in point cloud data. However, the segmentation model using multi-modal input faces some problems, such as the modal consistency problem and the model complexity problem. In this paper, we propose utilizing the idea of an Occupancy-based multi-view feature combination method to obtain the 3D information of the features of the two modalities independently. We also design a projection structure to obtain the three-axis features in different modalities according to the information, including the main view, side view, and top view features. We construct a module called Feature View Transform (FVT) that combines three-axis plane features with bias. The CNN neural network is used to replace attention mechanisms, reducing the dimensionality of the original three-dimensional space matrix, thereby reducing the parameter count and increasing the model’s speed. We used a bilinear mapping structure to fuse LiDAR and Camera features and complete the 3D semantic segmentation task. We validate the model on the NuScenes dataset and obtain competitive accuracy results while leading the way in efficiency evaluation metrics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Semantic Segmentation

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The effects of 17β-trenbolone and bisphenol A on sexual behavior and social dominance via the hypothalamic-pituitary-gonadal axis in male mice

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Journal of Environmental Sciences 2025年第5期151卷 54-67页

作者： Xiang Zuo Minghe Sun Huijuan Bai Shuhui Zhang Jialu Luan Qian Yu Zhenhua Fu Qili Zhao Mingzhu Sun Xin Zhao Xizeng Feng College of Life Science State Key Laboratory of Medicinal Chemical BiologyThe Key Laboratory of Bioactive MaterialsMinistry of EducationNankai UniversityTianjin 300071China Institute of Robotics&Automatic Information System College of Artificial IntelligenceNankai UniversityTianjin 300071China

17β-Trenbolone(17-TB)is well documented as an environmental endocrine disruptor in aquatic biological studies,but its effects on mammals remain poorly ***,17-TB acts as a hormone with properties similar to testosterone,and the consequences of juvenile exposure on adult social behavior remain *** A(BPA)acts as an estrogen-like hormone,compared to ***-week-old male Balb/c mice were exposed orally to 17-TB(100μg/(kg·day))and BPA(4 mg/(kg·day))for 28 *** of social interactions and a three-chamber test showed that 17-TB increased virility in male mice,intensified both male and female sexual behavior,and attracted and accepted female *** also increased social dominance through tube tests inmalemice and markedly activated the c-Fos^(+)immune response in themedial prefrontal cortex(mPFC)and basal amygdala(BLA).ELISA data showed that 17-TB and BPA exposure significantly affected serum gonadotropin-releasing hormone(GnRH),growth hormone(GH),estradiol(E2),and luteinizing hormone(LH)levels,as well as testicular lesions and androgen receptor(ARβ)and estrogen receptor(ERα)*** transcriptomic analysis further confirmed that could disrupt steroid synthesis and linoleic acid-related biometabolic *** findings suggest the influence of 17-TB and BPA exposure on sexual behavior and fertility in male mice,possibly through modulation of the hypothalamic-pituitary-gonadal *** study provides insights relevant to human reproductive health and neuro-social behavioral research,and the potential risk of environmental disturbances should not be overlooked.

关键词： 17β-Trenbolone(17-TB) Bisphenol A(BPA) hypothalamic-pituitary-gonadal axis(HPG) Sex hormones Social dominance Sexual behavior

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Epipolar Attention Field Transformers for Bird's Eye View Semantic Segmentation

Epipolar Attention Field Transformers for Bird's Eye View Se...

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2025 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2025

作者： Witte, Christian Behley, Jens Stachniss, Cyrill Raaijmakers, Marvin Cariad Se Germany University of Bonn Center for Robotics Germany Lamarr Institute for Machine Learning and Artificial Intelligence Germany

ISBN: (纸本)9798331510831

Spatial understanding of the semantics of the surroundings is a key capability needed by autonomous cars to enable safe driving decisions. Recently, purely vision-based solutions have gained increasing research interest. In particular, approaches extracting a bird's eye view (BEV) from multiple cameras have demonstrated great performance for spatial understanding. This paper addresses the dependency on learned positional encodings to correlate image and BEV feature map elements for transformer-based methods. We propose leveraging epipolar geometric constraints to model the relationship between cameras and the BEV by Epipolar Attention Fields. They are incorporated into the attention mechanism as a novel attribution term, serving as an alternative to learned positional encodings. Experiments show that our method EAFormer outperforms previous BEV approaches by 2% mIoU for map semantic segmentation and exhibits superior generalization capabilities compared to implicitly learning the camera configuration. © 2025 IEEE.

关键词： Semantic Segmentation

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Thin and Flexible Breeze-Sense Generators for Non-Contact Haptic Feedback in Virtual Reality

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Nano-Micro Letters 2025年第6期17卷 397-410页

作者： Kaijun Zhang Zhe Liu Yexi Zhou Zhaoyang Li Dazhe Zhao Xiao Guan Tianjun Lan Yanting Gong Bingpu Zhou Junwen Zhong Department of Electromechanical Engineering and Centre for Artificial Intelligence and Robotics University of MacaoMacao SAR 999078People’s Republic of China Joint Key Laboratory of the Ministry of Education Institute of Applied Physics and Materials EngineeringUniversity of MacaoMacao SAR 999078People’s Republic of China

In the realm of virtual reality(VR),haptic feedback is integral to enhance the immersive experience;yet,existing wearable devices predominantly rely on skin contact feedback,lacking options for compact and non-contact breeze-sense ***,we propose a compact and non-contact working model piezoelectret actuator for providing a gentle and safe breeze *** easy-fabricated and flexible breeze-sense generator with thickness around 1 mm generates air flow pressure up to~163 Pa,which is significantly sensed by human *** a typical demonstration,the breeze-sense generators array showcases its versatility by employing multiple coded modes for non-contact information *** thin thinness and good flexibility facilitate seamless integration with wearable VR setups,and the wearable arrays empower volunteers to precisely perceive the continuous and sudden breeze senses in the virtual *** work is expected to inspire developing new haptic feedback devices that play pivotal roles in human-machine interfaces for VR applications.

关键词： Virtual reality Wearable electronics Non-contact haptic feedback Breeze-sense Piezoelectret actuator

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Design of a Convertible Autonomous Sailboat

Design of a Convertible Autonomous Sailboat

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Lin, Bairun Liang, Cheng Zhang, Lianxin Qian, Huihuan Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China The Chinese University of HongKong Shenzhen China

ISBN: (纸本)9798350327182

Multihull sailboats have significantly improved stability but poor maneuverability compared to monohull sailboats under the same conditions. Therefore, this article proposes a convertible autonomous sailboat based on the transformation of an autonomous sailboat. This article analyzes and studies stability improvements that validate our design and analysis in calm and turbulent water. It turns out that in the absence of waves, compared to autonomous sailboats, our convertible autonomous sailboat has a speed loss in the range of 25% to 30%, but its stability improved by 84.13% to 88.77%. However, in the presence of waves, the velocity loss is only 15.56% to 24.44%, but the stability improved by 92.37% to 94.78% © 2023 IEEE.

关键词： Stability

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Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection 38

Voxel Mamba: Group-Free State Space Models for Point Cloud b...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhang, Guowen Fan, Lue He, Chenhang Lei, Zhen Zhang, Zhaoxiang Zhang, Lei The Hong Kong Polytechnic University Hong Kong Centre for Artificial Intelligence and Robotics HKISI CAS China Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China

Serialization-based methods, which serialize the 3D voxels and group them into multiple sequences before inputting to Transformers, have demonstrated their effectiveness in 3D object detection. However, serializing 3D voxels into 1D sequences will inevitably sacrifice the voxel spatial proximity. Such an issue is hard to be addressed by enlarging the group size with existing serialization-based methods due to the quadratic complexity of Transformers with feature sizes. Inspired by the recent advances of state space models (SSMs), we present a Voxel SSM, termed as Voxel Mamba, which employs a group-free strategy to serialize the whole space of voxels into a single sequence. The linear complexity of SSMs encourages our group-free design, alleviating the loss of spatial proximity of voxels. To further enhance the spatial proximity, we propose a Dual-scale SSM Block to establish a hierarchical structure, enabling a larger receptive field in the 1D serialization curve, as well as more complete local regions in 3D space. Moreover, we implicitly apply window partition under the group-free framework by positional encoding, which further enhances spatial proximity by encoding voxel positional information. Our experiments on Waymo Open Dataset and nuScenes dataset show that Voxel Mamba not only achieves higher accuracy than state-of-the-art methods, but also demonstrates significant advantages in computational efficiency. The source code is available at https://***/gwenzhang/Voxel-Mamba. © 2024 Neural information processing systems foundation. All rights reserved.

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Group UAV Navigation by Qualifying Human-Machine Decisions in Hybrid Reinforcement Learning

Group UAV Navigation by Qualifying Human-Machine Decisions i...

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2023 China Automation Congress, CAC 2023

作者： Li, Xuyang Fang, Jianwu Du, Kai Xue, Jianru Chang'An University Xi'an China Institute of Artificial Intelligence and Robotics Xi'An Jiaotong University Xi'an China

ISBN: (纸本)9798350303759

In this paper, we focus on the continuous control of Unmanned Aerial Vehicle (UAV) group in large-scale 3D complex environment based on deep reinforcement learning (DRL) method. The purpose is to make the UAV group safely reach the random target area from a certain starting point, and the flight height and speed are variable during the navigation process. In this paper, a DRL framework combining the human-in-the-loop method is designed. The UAV group is preformed into a mobile whole, and the sensor data of the UAV group is directly mapped to the control signal. The role of human-in-the-loop is to switch the human-machine control right if necessary, so that humans can intervene and correct the dangerous actions of the agent. Based on this framework, an improved Actor-Critic structure is designed, and the policy and value network of the original structure are modified accordingly. We verify the success rate and time efficiency of different numbers of UAV group navigation in the urban environment. The experimental results show that this method can reduce the training convergence time and improve the efficiency and success rate of navigation. © 2023 IEEE.

关键词： Reinforcement learning

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Temporally Consistent 3D Human Motion Estimation from a Video 7

Temporally Consistent 3D Human Motion Estimation from a Vide...

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7th International Conference on Computer Graphics and Virtuality, ICCGV 2024

作者： Zhang, Zhaobing Liu, Yuehu Wang, Shaorong Yan, Yuanfeng School of Software Engineering Xi’an Jiaotong University Xi’an China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China

ISBN: (数字)9781510679788

ISBN: (纸本)9781510679771

It is still difficult to accurately extract smooth and consistent 3D human motion from video footage over time. While some existing techniques have achieved favorable outcomes by utilizing the combined features of consecutive frames, many of them compromise accuracy in order to reduce jitter or do not have a complete understanding of the temporal nature of human movement. To this end, we model the natural smoothing properties in body motion by learning the long-range temporal relationship between the kinematic features of the human body in the video and the enhanced current frame features. First, we use the velocity and acceleration of key points to effectively capture temporal features as our temporal motion prior, and then we have created a module that uses a hierarchical attention mechanism to improve the representation of the current frame by selectively focusing on important temporal information from both past and future frames. This enhances the correlation between frames and improves the overall quality of the feature representation. Ultimately these two parts of features are aggregated together through a global motion aware network and linear fusion is performed to obtain the final accurate 3D human motion. © 2024 SPIE.

关键词： Acceleration

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Layer-Animate for Transparent Video Generation

Layer-Animate for Transparent Video Generation

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Bai, Jingqi Zhou, Jingkai Wang, Benzhi Chen, Weihua Yang, Yang Lei, Zhen Wang, Fan State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Chinese Academy of Sciences China Alibaba Group China

ISBN: (纸本)9798350368741

Transparent videos with alpha channels play a crucial role in film production, advertising, and augmented reality fields. However, there is currently no available method for producing transparent videos. Traditional methods are time-consuming and labor-intensive, and employing alternative approaches for this task will result in inaccurate transparent regions, constrained motion, and artifacts. To address these challenges, we propose Layer-Animate, the first method capable of generating transparent videos. Our method comprises two stages: in the first stage, transparent images are generated as the base images to provide content and transparency information for the next stage. In the second stage, Inter-Frame Attention is applied to decouple content from motion, enabling the motion module to focus better on action. Layer-Animate is the first method used to generate transparent videos with accurate transparent regions, sufficient motion, and no artifacts, as demonstrated by notable improvements in qualitative and quantitative metrics. © 2025 IEEE.

关键词： deep generative models diffusion models transparent videos video generation

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Enhanced-Coupling Based Nonlinear Control for Aerial Transportation Systems with Variable-Length Cable

Enhanced-Coupling Based Nonlinear Control for Aerial Transpo...

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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Yu, Hai Wu, Shizhen Liang, Xiao Fang, Yongchun Han, Jianda Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China

ISBN: (纸本)9789811966125

An enhanced-coupling based control law for the aerial transportation system (ATS) with variable-length cable is studied in this paper. A composite position signal is utilized to construct the Lyapunov function candidate, from which the final control law is designed. Subsequently, the asymptotic stability result is given through LaSalle’s invariance theorem. Simulations present that the proposed control law can achieve simultaneously quadrotor positioning, cable length adjusting and payload swing elimination. Specially, the enhanced-coupling based control scheme presents satisfactory anti-swing ability compared with the classical PD based method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cables

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