Self-Supervised AI-Generated Image Detection: A Camera Metadata Perspective [0.03%]
自监督人工智能生成图像检测：相机元数据视角
Nan Zhong,Mian Zou,Yiran Xu et al.
Nan Zhong et al.
The proliferation of AI-generated imagery poses escalating challenges for multimedia forensics, yet many existing detectors depend on assumptions about the internals of specific generative models, limiting their cross-model applicability. W...
VRP-UDF: Towards Unbiased Learning of Unsigned Distance Functions from Multi-view Images with Volume Rendering Priors [0.03%]
基于体积渲染的多视角图像无偏无符号距离函数学习
Wenyuan Zhang,Chunsheng Wang,Kanle Shi et al.
Wenyuan Zhang et al.
Unsigned distance functions (UDFs) have been a vital representation for open surfaces. With different differentiable renderers, current methods are able to train neural networks to infer a UDF by minimizing the rendering errors with the UDF...
Xiaoyang Xu,Wenzhe Yi,Juan Wang et al.
Xiaoyang Xu et al.
Split Learning (SL) is a distributed learning framework that has gained popularity for its privacy-preserving nature and low computational demands. However, recent studies have the potential that a server adversary to carry out inference at...
A Gift from the Integration of Discriminative and Diffusion-based Generative Learning: Boundary Refinement Remote Sensing Semantic Segmentation [0.03%]
基于判别式和扩散生成学习集成的遥感语义分割边界优化方法研究赠礼
Hao Wang,Keyan Hu,Xin Guo et al.
Hao Wang et al.
Remote sensing semantic segmentation must address both what the ground objects are within an image and where they are located. Consequently, segmentation models must ensure not only the semantic correctness of large-scale patches (low-frequ...
Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Driving [0.03%]
自扩张增强精化在端到端自动驾驶中的应用
Haochen Liu,Tianyu Li,Haohan Yang et al.
Haochen Liu et al.
End-to-end autonomous driving has emerged as a promising paradigm for directly mapping sensor inputs to planning maneuvers using learning-based modular integrations. However, existing imitation learning (IL)-based models suffer from general...
Gengyun Jia,Xin Ma,Bing-Kun Bao
Gengyun Jia
Ordinal regression aims to predict ordered classes. Existing methods mainly focus on label distribution shapes and feature distance relationships, while the directional characteristics in the representation space remain underexplored. In th...
Kun Xiang,Zhili Liu,Terry Jingchen Zhang et al.
Kun Xiang et al.
In this paper, we address the challenging task of multimodal reasoning by incorporating the notion of "slow thinking" into multimodal large language models (MLLMs). Our core idea is that models can learn to adaptively use different levels o...
Liwen Hu,Yijia Guo,Mianzhi Liu et al.
Liwen Hu et al.
High-speed vision tasks have long been a challenge in computer vision. Recently, the spike camera has shown great potential in these tasks due to its high temporal resolution. Unlike traditional cameras, it emits asynchronous spike signals ...
Revisiting 360 Depth Estimation With PanoGabor: A New Fusion Perspective [0.03%]
基于PanoGabor的全方位深度估计融合方法研究
Zhijie Shen,Chunyu Lin,Lang Nie et al.
Zhijie Shen et al.
Depth estimation from a monocular 360 image is important to the perception of the entire 3D environment. However, the inherent distortion and large field of view (FoV) in 360 images pose great challenges for this task. To this end, existing...
An Efficient Multi-Estimation-Based Parameter Centroid Decision Via Linear Regression Approach [0.03%]
基于线性回归的高效多估计参数重心决策方法
Yeongyu Choi,Fabien Moutarde,Ju H Park et al.
Yeongyu Choi et al.
We propose a novel post-processing approach for the local optimization of Locally Optimized RANdom SAmple Consensus (LO-RANSAC), called the Multi-Estimation-based Parameter Centroid (MEPC) decision. It is observed that the optimal threshold...