Accurate Industrial Anomaly Detection and Localization using Weakly-Supervised Residual Transformers [0.03%]
基于弱监督残差变换器的精确工业异常检测与定位
Hanxi Li,Jingqi Wu,Deyin Liu et al.
Hanxi Li et al.
Recent advancements in industrial anomaly detection (AD) have demonstrated that incorporating a small number of anomalous samples during training can significantly enhance accuracy. However, this improvement often comes at the cost of exten...
Binqian Xu,Xiangbo Shu,Jiachao Zhang et al.
Binqian Xu et al.
Contrastive learning facilitates the acquisition of informative skeleton representations for unsupervised action recognition by leveraging effective positive and negative sample pairs. However, most existing methods construct these pairs th...
Cross360: 360° Monocular Depth Estimation via Cross Projections Across Scales [0.03%]
基于跨尺度交叉投影的单目360度深度估计方法
Kun Huang,Fang-Lue Zhang,Neil Dodgson
Kun Huang
360° depth estimation is a challenging research problem due to the difficulty of finding a representation that both preserves global continuity and avoids distortion in spherical images. Existing methods attempt to leverage complementary i...
Incorporating Uncertainty-Guided and Top-k Codebook Matching for Real-World Blind Image Super-Resolution [0.03%]
基于不确定性指导和Top-k码本匹配的盲式图像超分辨率方法
Weilei Wen,Tianyi Zhang,Qianqian Zhao et al.
Weilei Wen et al.
Recent advancements in codebook-based real image super-resolution (SR) have shown promising results in real-world applications. The core idea involves matching high-quality image features from a codebook based on low-resolution (LR) image f...
SuperCL: Superpixel Guided Contrastive Learning for Medical Image Segmentation Pre-training [0.03%]
基于超像素的对比学习在医学图像分割中的预训练（SuperCL）
Shuang Zeng,Lei Zhu,Xinliang Zhang et al.
Shuang Zeng et al.
Medical image segmentation is a critical yet challenging task, primarily due to the difficulty of obtaining extensive datasets of high-quality, expert-annotated images. Contrastive learning presents a potential but still problematic solutio...
AvatarMakeup: Realistic Makeup Transfer for 3D Animatable Head Avatars [0.03%]
_avatarmakeup：用于三维可动画头像的逼真化妆品转移_
Yiming Zhong,Xiaolin Zhang,Ligang Liu et al.
Yiming Zhong et al.
Similar to facial beautification in real life, 3D virtual avatars require personalized customization to enhance their visual appeal, yet this area remains insufficiently explored. Although current 3D Gaussian editing methods can be adapted ...
MambaFedCD: Spatial-Spectral-Temporal Collaborative Mamba-Based Active Federated Hyperspectral Change Detection [0.03%]
基于曼巴的主动联邦高光谱变化检测的空间-光谱- temporal协作(MambaFedCD)
Jiahui Qu,Jingyu Zhao,Wenqian Dong et al.
Jiahui Qu et al.
Hyperspectral image (HSI) change detection is a technique that can identify the changes occurring between the bitemporal HSIs covering the same geographic area. The field of change detection has witnessed the proposal and successful impleme...
Frequency-Decomposed Interaction Network for Stereo Image Restoration [0.03%]
基于频率分解的交互网络在立体图像恢复中的应用研究
Xianmin Tian,Jin Xie,Ronghua Xu et al.
Xianmin Tian et al.
Stereo image restoration in adverse environments, such as low-light conditions, rain, and low resolution, requires effective exploitation of cross-view complementary information to recover degraded visual content. In monocular image restora...
Bidirectional Cross-Modal Collaborative Alignment via Semantic-Guided Visual Embeddings for Partially Relevant Video Retrieval [0.03%]
基于语义引导的视觉嵌入的双向跨模态协作对齐的不完全相关视频检索方法
Huafeng Li,Jialong Zhao,Yafei Zhang et al.
Huafeng Li et al.
Partially Relevant Video Retrieval (PRVR) aims to retrieve videos that match a given textual query only partially. This task is inherently challenging due to the modality gap between text and video, which is further exacerbated by the parti...
MDA-MAA: A Collaborative Augmentation Approach for Generalizing Cross-Domain Retrieval [0.03%]
MDA-MAA：一种协作增强方法，用于泛化跨域检索模型
Ming Jin,Richang Hong
Ming Jin
In video-text cross-domain retrieval tasks, the generalization ability of the retrieval models is key to improving their performance and is crucial for enhancing their practical applicability. However, existing retrieval models exhibit sign...