English(EN)ArchSym: Detecting 3D-Grounded Architectural Symmetries in the Wild
计算机视觉研究推动多模态理解和鲁棒分割
作者PulseAugur 编辑部·[13 个来源]·
研究人员开发了 WeatherSeg，这是一个半监督分割框架，旨在通过使用双教师-学生模型进行知识蒸馏和分类器权重更新机制，来改善恶劣天气条件下自动驾驶的感知能力。另外，为多摄像头系统提出了一种新的仅姿态几何约束，以提高视觉导航和 3D 场景重建中捆绑调整的计算效率。另一项进展通过将摄像头嵌入校准目标中，实现了多投影仪校准的可扩展性限制，从而可以同时估计投影仪参数。此外，DeepTaxon 提供了一个检索增强的多模态框架，用于生物多样性研究中的统一物种识别和发现，而 TSMNet 将文本监督与视觉表示相结合，用于遥感中的开放词汇语义分割。
AI
arXiv:2604.26031v1 Announce Type: new Abstract: This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, which evaluates state-of-the-art models under highly un…
arXiv:2604.23704v1 Announce Type: new Abstract: Multi-camera systems offer rich observation capabilities for visual navigation and 3D scene reconstruction; however, the resulting feature redundancy often compromises computational efficiency. This challenge is particularly pronoun…
arXiv:2604.24024v1 Announce Type: new Abstract: Conventional multi-projector calibration requires projecting and capturing structured light patterns for each projector sequentially, causing calibration time and effort to increase linearly with the number of projectors. This scala…
arXiv:2604.24029v1 Announce Type: new Abstract: Identifying species in biology among tens of thousands of visually similar taxa while discovering unknown species in open-world environments remains a fundamental challenge in biodiversity research. Current methods treat identificat…
arXiv cs.CV
TIER_1English(EN)·Jinkun Dai, Yuanxin Ye, Peng Tang, Tengfeng Tang, Xianping Ma, Jing Xiao, Mi Wang·
arXiv:2604.24125v1 Announce Type: new Abstract: Semantic segmentation of multi-modal remote sensing imagery plays a pivotal role in land use/land cover (LULC) mapping, environmental monitoring, and precision earth observation. Current multi-modal approaches mainly focus on integr…
arXiv:2604.24167v1 Announce Type: new Abstract: Implicit neural representations (INRs) are increasingly being used as tools to map coordinates to signals, encompassing applications from neural fields to texture compression, shape representations, and beyond. Most INR methods are …
Implicit neural representations (INRs) are increasingly being used as tools to map coordinates to signals, encompassing applications from neural fields to texture compression, shape representations, and beyond. Most INR methods are based on using high-dimensional projections of t…
Semantic segmentation of multi-modal remote sensing imagery plays a pivotal role in land use/land cover (LULC) mapping, environmental monitoring, and precision earth observation. Current multi-modal approaches mainly focus on integrating complementary visual modalities, yet negle…
Identifying species in biology among tens of thousands of visually similar taxa while discovering unknown species in open-world environments remains a fundamental challenge in biodiversity research. Current methods treat identification and discovery as separate problems, with cla…
Conventional multi-projector calibration requires projecting and capturing structured light patterns for each projector sequentially, causing calibration time and effort to increase linearly with the number of projectors. This scalability bottleneck has long limited the deploymen…
arXiv cs.CV
TIER_1English(EN)·Hanyu Chen, Ruojin Cai, Steve Marschner, Noah Snavely·
arXiv:2604.22202v1 Announce Type: new Abstract: Symmetry detection is a fundamental problem in computer vision, and symmetries serve as powerful priors for downstream tasks. However, existing learning-based methods for detecting 3D symmetries from single images have been almost e…
Symmetry detection is a fundamental problem in computer vision, and symmetries serve as powerful priors for downstream tasks. However, existing learning-based methods for detecting 3D symmetries from single images have been almost exclusively trained and evaluated on object-centr…
