Výsledky vyhledávání - "3D from multi-view and sensors"

Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields Autor Barron, Jonathan T., Mildenhall, Ben, Verbin, Dor, Srinivasan, Pratul P., Hedman, Peter

“…Though neural radiance fields (NeRF) have demon-strated impressive view synthesis results on objects and small bounded regions of space, they struggle on…”
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Plenoxels: Radiance Fields without Neural Networks Autor Fridovich-Keil, Sara, Yu, Alex, Tancik, Matthew, Chen, Qinhong, Recht, Benjamin, Kanazawa, Angjoo

“…We introduce Plenoxels (plenoptic voxels), a systemfor photorealistic view synthesis. Plenoxels represent a scene as a sparse 3D grid with spherical harmonics…”
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Block-NeRF: Scalable Large Scene Neural View Synthesis Autor Tancik, Matthew, Casser, Vincent, Yan, Xinchen, Pradhan, Sabeek, Mildenhall, Ben P., Srinivasan, Pratul, Barron, Jonathan T., Kretzschmar, Henrik

“…We present Block-NeRF, a variant of Neural Radiance Fields that can represent large-scale environments. Specifically, we demonstrate that when scaling NeRF to…”
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Depth-supervised NeRF: Fewer Views and Faster Training for Free Autor Deng, Kangle, Liu, Andrew, Zhu, Jun-Yan, Ramanan, Deva

“…A commonly observed failure mode of Neural Radiance Field (NeRF) is fitting incorrect geometries when given an insufficient number of input views. One…”
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Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields Autor Verbin, Dor, Hedman, Peter, Mildenhall, Ben, Zickler, Todd, Barron, Jonathan T., Srinivasan, Pratul P.

“…Neural Radiance Fields (NeRF) is a popular view synthesis technique that represents a scene as a continuous volumetric function, parameterized by multilayer…”
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HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Video Autor Weng, Chung-Yi, Curless, Brian, Srinivasan, Pratul P., Barron, Jonathan T., Kemelmacher-Shlizerman, Ira

“…We introduce a free-viewpoint rendering method - HumanNeRF - that works on a given monocular video of a human performing complex body motions, e.g. a video…”
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Neural 3D Video Synthesis from Multi-view Video Autor Li, Tianye, Slavcheva, Mira, Zollhoefer, Michael, Green, Simon, Lassner, Christoph, Kim, Changil, Schmidt, Tanner, Lovegrove, Steven, Goesele, Michael, Newcombe, Richard, Lv, Zhaoyang

“…We propose a novel approach for 3D video synthesis that is able to represent multi-view video recordings of a dynamic real-world scene in a compact, yet…”
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Stratified Transformer for 3D Point Cloud Segmentation Autor Lai, Xin, Liu, Jianhui, Jiang, Li, Wang, Liwei, Zhao, Hengshuang, Liu, Shu, Qi, Xiaojuan, Jia, Jiaya

“…3D point cloud segmentation has made tremendous progress in recent years. Most current methods focus on aggregating local features, but fail to directly model…”
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DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection Autor Li, Yingwei, Yu, Adams Wei, Meng, Tianjian, Caine, Ben, Ngiam, Jiquan, Peng, Daiyi, Shen, Junyang, Lu, Yifeng, Zhou, Denny, Le, Quoc V., Yuille, Alan, Tan, Mingxing

“…Lidars and cameras are critical sensors that provide complementary information for 3D detection in autonomous driving. While prevalent multi-modal methods…”
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CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields Autor Wang, Can, Chai, Menglei, He, Mingming, Chen, Dongdong, Liao, Jing

“…We present CLIP-NeRF, a multi-modal 3D object manipulation method for neural radiance fields (NeRF). By leveraging the joint language-image embedding space of…”
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NICE-SLAM: Neural Implicit Scalable Encoding for SLAM Autor Zhu, Zihan, Peng, Songyou, Larsson, Viktor, Xu, Weiwei, Bao, Hujun, Cui, Zhaopeng, Oswald, Martin R., Pollefeys, Marc

“…Neural implicit representations have recently shown encouraging results in various domains, including promising progress in simultaneous localization and…”
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TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers Autor Bai, Xuyang, Hu, Zeyu, Zhu, Xinge, Huang, Qingqiu, Chen, Yilun, Fu, Hangbo, Tai, Chiew-Lan

“…LiDAR and camera are two important sensors for 3D object detection in autonomous driving. Despite the increasing popularity of sensor fusion in this field, the…”
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Dense Depth Priors for Neural Radiance Fields from Sparse Input Views Autor Roessle, Barbara, Barron, Jonathan T., Mildenhall, Ben, Srinivasan, Pratul P., Niebner, Matthias

“…Neural radiance fields (NeRF) encode a scene into a neural representation that enables photo-realistic rendering of novel views. However, a successful…”
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Point-NeRF: Point-based Neural Radiance Fields Autor Xu, Qiangeng, Xu, Zexiang, Philip, Julien, Bi, Sai, Shu, Zhixin, Sunkavalli, Kalyan, Neumann, Ulrich

“…Volumetric neural rendering methods like NeRF [34] generate high-quality view synthesis results but are optimized per-scene leading to prohibitive…”
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NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images Autor Mildenhall, Ben, Hedman, Peter, Martin-Brualla, Ricardo, Srinivasan, Pratul P., Barron, Jonathan T.

“…Neural Radiance Fields (NeRF) is a technique for high quality novel view synthesis from a collection of posed input images. Like most view synthesis methods,…”
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Geometric Transformer for Fast and Robust Point Cloud Registration Autor Qin, Zheng, Yu, Hao, Wang, Changiian, Guo, Yulan, Peng, Yuxing, Xu, Kai

“…We study the problem of extracting accurate correspondences for point cloud registration. Recent keypoint-free methods bypass the detection of repeatable…”
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PointCLIP: Point Cloud Understanding by CLIP Autor Zhang, Renrui, Guo, Ziyu, Zhang, Wei, Li, Kunchang, Miao, Xupeng, Cui, Bin, Qiao, Yu, Gao, Peng, Li, Hongsheng

“…Recently, zero-shot and few-shot learning via Contrastive Vision-Language Pre-training (CLIP) have shown inspirational performance on 2D visual recognition,…”
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HeadNeRF: A Realtime NeRF-based Parametric Head Model Autor Hong, Yang, Peng, Bo, Xiao, Haiyao, Liu, Ligang, Zhang, Juyong

“…In this paper, we propose HeadNeRF, a novel NeRF-based parametric head model that integrates the neural radiance field to the parametric representation of the…”
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Embracing Single Stride 3D Object Detector with Sparse Transformer Autor Fan, Lue, Pang, Ziqi, Zhang, Tianyuan, Wang, Yu-Xiong, Zhao, Hang, Wang, Feng, Wang, Naiyan, Zhang, Zhaoxiang

“…In LiDAR-based 3D object detection for autonomous driving, the ratio of the object size to input scene size is significantly smaller compared to 2D detection…”
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Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation Autor Kundu, Abhijit, Genova, Kyle, Yin, Xiaoqi, Fathi, Alireza, Pantofaru, Caroline, Guibas, Leonidas, Tagliasacchi, Andrea, Dellaert, Frank, Funkhouser, Thomas

“…We present Panoptic Neural Fields (PNF), an object-aware neural scene representation that decomposes a scene into a set of objects (things) and background…”
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