作者: spinal-stenosis 時間: 2025-3-21 22:00
,Structure and?Motion from?Casual Videos,he camera is often roughly stationary (not much parallax), and a large portion of the video may contain moving objects. Under such conditions, state-of-the-art SfM methods tend to produce erroneous results, often failing entirely. To address these issues, we propose CasualSAM, a method to estimate c作者: 可能性 時間: 2025-3-22 03:00
,What Matters for?3D Scene Flow Network, scene flow estimation, and it encodes the point motion between two consecutive frames. Thus, it is critical for the flow embeddings to capture the correct overall direction of the motion. However, previous works only search locally to determine a soft correspondence, ignoring the distant points tha作者: 歪曲道理 時間: 2025-3-22 06:54 作者: FRAX-tool 時間: 2025-3-22 11:11 作者: Seminar 時間: 2025-3-22 13:52
,GraphCSPN: Geometry-Aware Depth Completion via?Dynamic GCNs,as a wide range of applications from robotics to autonomous driving. However, the 3D nature of sparse-to-dense depth completion has not been fully explored by previous methods. In this work, we propose a . .onvolution based .patial .ropagation .etwork (.) as a general approach for depth completion. 作者: Seminar 時間: 2025-3-22 17:47
,Objects Can Move: 3D Change Detection by?Geometric Transformation Consistency,ose a 3D object discovery method that is based only on scene changes. Our method does not need to encode any assumptions about what is an object, but rather discovers objects by exploiting their coherent move. Changes are initially detected as differences in the depth maps and segmented as objects i作者: Phonophobia 時間: 2025-3-22 21:37 作者: 僵硬 時間: 2025-3-23 04:38
,Beyond Periodicity: Towards a?Unifying Framework for?Activations in?Coordinate-MLPs, grid-based approximations. However, coordinate-MLPs with ReLU activations, in their rudimentary form, demonstrate poor performance in representing signals with high fidelity, promoting the need for positional embedding layers. Recently, Sitzmann .?[.] proposed a sinusoidal activation function that 作者: 即席演說 時間: 2025-3-23 06:34
,Deforming Radiance Fields with?Cages,is used for scene manipulation or animation. In this paper, we propose a method that enables a new type of deformation of the radiance field: free-form radiance field deformation. We use a triangular mesh that encloses the foreground object called . as an interface, and by manipulating the cage vert作者: 人造 時間: 2025-3-23 11:56 作者: 逢迎白雪 時間: 2025-3-23 13:58
,MODE: Multi-view Omnidirectional Depth Estimation with?360,?Cameras, maps from different camera pairs via omnidirectional stereo matching and then fuses the depth maps to achieve robustness against mud spots, water drops on camera lenses, and glare caused by intense light. We adopt spherical feature learning to address the distortion of panoramas. In addition, a syn作者: 邪惡的你 時間: 2025-3-23 19:19 作者: moratorium 時間: 2025-3-24 00:39
,Gaussian Activated Neural Radiance Fields for?High Fidelity Reconstruction and Pose Estimation,s require accurate prior camera poses. Although approaches for jointly recovering the radiance field and camera pose exist, they rely on a cumbersome coarse-to-fine auxiliary positional embedding to ensure good performance. We present Gaussian Activated Neural Radiance Fields (GARF), a new positiona作者: modest 時間: 2025-3-24 04:59 作者: infarct 時間: 2025-3-24 08:05 作者: 松馳 時間: 2025-3-24 14:20 作者: Kindle 時間: 2025-3-24 15:07 作者: Cosmopolitan 時間: 2025-3-24 21:52 作者: 平項山 時間: 2025-3-25 00:14
,Objects Can Move: 3D Change Detection by?Geometric Transformation Consistency,f they undergo rigid motions. A graph cut optimization propagates the changing labels to geometrically consistent regions. Experiments show that our method achieves state-of-the-art performance on the 3RScan dataset against competitive baselines. The source code of our method can be found at ..作者: Sigmoidoscopy 時間: 2025-3-25 05:35 作者: lipoatrophy 時間: 2025-3-25 09:33 作者: 必死 時間: 2025-3-25 12:01
https://doi.org/10.1057/9780230597686f they undergo rigid motions. A graph cut optimization propagates the changing labels to geometrically consistent regions. Experiments show that our method achieves state-of-the-art performance on the 3RScan dataset against competitive baselines. The source code of our method can be found at ..作者: 會議 時間: 2025-3-25 18:06
The Economics of Transaction Costsl embedding-free neural radiance field architecture – employing Gaussian activations – that is competitive with the current state-of-the-art in terms of high fidelity reconstruction and pose estimation.作者: Cardioversion 時間: 2025-3-26 00:01 作者: Engaging 時間: 2025-3-26 02:46
0302-9743 ruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation..978-3-031-19826-7978-3-031-19827-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 一再困擾 時間: 2025-3-26 05:45 作者: SUGAR 時間: 2025-3-26 10:41
The Determinants of Union Staff Salariesmbining appearance with a multi-view geometric prior, we enable, for the first time, the joint learning of appearance and explicit hair geometry from a multi-view setup. We demonstrate the efficacy of our approach in terms of fidelity and efficiency for various hairstyles.作者: ARCH 時間: 2025-3-26 16:22
The Economics of Transaction Costs points from the deformed space to the canonical space, thus enabling the rendering of the deformed scene. The deformation results of the synthetic datasets and the real-world datasets demonstrate the effectiveness of our approach. Project page: ..作者: muscle-fibers 時間: 2025-3-26 19:47 作者: myelography 時間: 2025-3-26 23:45
The Economics of Transaction Costsorld applications by refining the camera poses and point cloud obtained from a real-time SLAM system. Finally, employing our framework in a neural rendering setting optimizes both the point cloud and network parameters, highlighting the framework’s ability to enhance data driven approaches.作者: SKIFF 時間: 2025-3-27 04:30 作者: hypnotic 時間: 2025-3-27 06:41 作者: dendrites 時間: 2025-3-27 09:53 作者: hurricane 時間: 2025-3-27 14:15 作者: intangibility 時間: 2025-3-27 19:30
,MODE: Multi-view Omnidirectional Depth Estimation with?360,?Cameras,esults show that the proposed framework generates reliable results in both synthetic and real-world environments, and it achieves state-of-the-art performance on different datasets. The code and data are available at ..作者: figment 時間: 2025-3-28 01:01 作者: medieval 時間: 2025-3-28 05:13
Class-Incremental Novel Class Discovery,gy that simultaneously clusters novel categories and trains a joint classifier for both the base and novel classes. This makes our method able to operate in a class-incremental setting. Our experiments, conducted on three common benchmarks, demonstrate that our method significantly outperforms state-of-the-art approaches. Code is available at ..作者: 補充 時間: 2025-3-28 06:45
Conference proceedings 2022on, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022..?.The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement lear作者: Preamble 時間: 2025-3-28 12:58 作者: 尾隨 時間: 2025-3-28 14:37
The Relative Wage Effect of French Unionshe camera is often roughly stationary (not much parallax), and a large portion of the video may contain moving objects. Under such conditions, state-of-the-art SfM methods tend to produce erroneous results, often failing entirely. To address these issues, we propose CasualSAM, a method to estimate c作者: Cirrhosis 時間: 2025-3-28 19:21 作者: plasma 時間: 2025-3-29 01:42 作者: 障礙 時間: 2025-3-29 05:07
The Determinants of Union Staff Salariesr model can be rendered in real-time from any viewpoint with high-fidelity view-dependent effects. Our model achieves intuitive shape and style control unlike volumetric counterparts. To enable these properties, we propose a novel hair representation based on a neural scalp texture that encodes the 作者: 人工制品 時間: 2025-3-29 08:31
https://doi.org/10.1057/9780230597686as a wide range of applications from robotics to autonomous driving. However, the 3D nature of sparse-to-dense depth completion has not been fully explored by previous methods. In this work, we propose a . .onvolution based .patial .ropagation .etwork (.) as a general approach for depth completion. 作者: 無彈性 時間: 2025-3-29 12:36 作者: 槍支 時間: 2025-3-29 18:32 作者: Urea508 時間: 2025-3-29 22:41 作者: magnanimity 時間: 2025-3-30 02:10 作者: septicemia 時間: 2025-3-30 07:23 作者: CRATE 時間: 2025-3-30 09:33 作者: NATAL 時間: 2025-3-30 12:26
https://doi.org/10.1057/9780230597686t to address this challenge by using objectness regions to guide the pose estimation problem rather than explicit semantic object detections. We propose Pose Refiner Network (PoserNet) a light-weight Graph Neural Network to refine the approximate pair-wise relative camera poses. PoserNet exploits as作者: verdict 時間: 2025-3-30 18:27
The Economics of Transaction Costss require accurate prior camera poses. Although approaches for jointly recovering the radiance field and camera pose exist, they rely on a cumbersome coarse-to-fine auxiliary positional embedding to ensure good performance. We present Gaussian Activated Neural Radiance Fields (GARF), a new positiona作者: Genetics 時間: 2025-3-31 00:09
The Economics of Transaction Costsbased on surface splatting. Our framework models the contribution of a point to the rendered image as a probability distribution. We derive an unbiased approximative gradient for the rendering function within this model. To efficiently evaluate the proposed sample estimate, we introduce a tree-based作者: NOMAD 時間: 2025-3-31 04:04
The Economics of Transaction CostsWhile traditional shape-from-shadow (SfS) algorithms reconstruct geometry from shadows, they assume a fixed scanning setup and fail to generalize to complex scenes. Neural rendering algorithms, on the other hand, rely on photometric consistency between RGB images, but largely ignore physical cues su作者: Parameter 時間: 2025-3-31 05:17
Elements of Industrial Organizationelled data set by leveraging a pre-trained model that has been trained on a labelled data set containing disjoint yet related categories. Apart from discovering novel classes, we also aim at preserving the ability of the model to recognize previously seen base categories. Inspired by rehearsal-based作者: assail 時間: 2025-3-31 11:37
Computer Vision – ECCV 2022978-3-031-19827-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Customary 時間: 2025-3-31 13:59 作者: 橫截,橫斷 時間: 2025-3-31 18:10 作者: Militia 時間: 2025-4-1 00:38 作者: needle 時間: 2025-4-1 04:56
SimpleRecon: 3D Reconstruction Without 3D Convolutions,ined with 2) the integration of keyframe and geometric metadata into the cost volume which allows informed depth plane scoring. Our method achieves a significant lead over the current state-of-the-art for depth estimation and close or better for 3D reconstruction on ScanNet and 7-Scenes, yet still a作者: BULLY 時間: 2025-4-1 07:55
,Structure and?Motion from?Casual Videos,on reprojection error. Our method sets a new state-of-the-art for pose and depth estimation on the Sintel dataset, and produces high-quality results for the DAVIS dataset where most prior methods fail to produce usable camera poses.作者: infarct 時間: 2025-4-1 10:48
,What Matters for?3D Scene Flow Network, design choices in key components of the 3D scene flow network, including the point similarity calculation, input elements of predictor, and predictor & refinement level design. After carefully choosing the most effective designs, we are able to present a model that achieves the state-of-the-art per作者: 十字架 時間: 2025-4-1 14:50 作者: tariff 時間: 2025-4-1 21:20 作者: 整潔漂亮 時間: 2025-4-2 00:00 作者: Adornment 時間: 2025-4-2 04:45
