Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection Jinyuan Liu†, Xin Fan‡,∗ Zhanbo Huang‡, Guanyao Wu‡, Risheng Liu‡,§, Wei Zhong‡, Zhongxuan L...
a growing number of approaches have been proposed to guide the generation of drug-like compounds given the information of target proteins, stemming from creative artificial intelligence techniques such as autoregressive models11,12,13,14,15, generative adversarial networks (GAN)16, variational autoencode...
Sun, J., Yao, W., Jiang, T., Wang, D., Chen, X.: Differential evolution based dual adversarial camouflage: fooling human eyes and object detectors. Neural Netw.Netw. 163, 256–271 (2023) Article Google Scholar Liu, Y., Wang, C.Q., Zhou, Y.J.: Camouflaged people detection based...
developed a new framework to robustly detect underwater seafood by integrating a generative adversarial network into a standard Faster R-CNN22. However,the method has a complex network structure and a high parametric load. In contrast, the single-stage framework avoids the use of region suggestions...
we design a dual equivariant diffusion model for learning and generating the binding molecule geometry. Based on our previous model MDM15, we devise two equivariant kernels to simulate the local chemical bonded graph and the global distant graph. In order to ensure the relative distance between the...
Dual discriminator generative adversarial network for video anomaly detection. IEEE Access, 8:88170±88176, 2020. [21] Hyunjong Park, Jongyoun Noh, and Bumsub Ham. Learning memory-guided normality for anomaly detection. In Proceed- ings of the IEEE/CVF Conference ...
A machine learning model is utilized to generate a representation of at least a portion of an environment surrounding the vehicle using sensor data from one or more sensors of the vehicle. At least a portion of a path to a target location corresponding to the received geographical location is ...
Defense against adversarial attacks via textual embeddings based on semantic associative field In this paper, we propose a textual adversarial defense method against word-level adversarial attacks via textual embedding based on the semantic associative ... J Huang,L Chen - 《Neural Computing & Applicat...
Zhao, L., et al.: Learning view-disentangled human pose representation by contrastive cross-view mutual information maximization. In: CVPR (2021) Google Scholar Zheng, K., Liu, W., He, L., Mei, T., Luo, J., Zha, Z.J.: Group-aware label transfer for domain adaptive person re-ident...
False Alarm: Adversarial Learning for Small Object Segmentation in Infrared Images. In Proceedings of the International Conference on Computer Vision 2019, Seoul, Republic of Korea, 27 October–2 November 2019; pp. 8508–8517. [Google Scholar] Shi, M.; Shi, M.; Wang, H. Infrared Dim and ...