作者: 遺傳學(xué) 時(shí)間: 2025-3-21 21:44
K. F. Walker,R. J. Shiel,P. L. Cadwalladeraverage, . brings down reconstruction error by 30% over SPR and by 270%+ over deep learning based SotA methods) at the cost of longer computation times and a slight increase in small-scale topological noise in some cases. Our source code, pre-trained model, and dataset are available at: ..作者: Soliloquy 時(shí)間: 2025-3-22 03:36 作者: NAUT 時(shí)間: 2025-3-22 07:02 作者: entreat 時(shí)間: 2025-3-22 10:10
Applied Aspects of Temporary Waters,l and temporal features of VSOD. Furthermore, our semi-curriculum learning design enables the first online refinement strategy for VSOD, which allows exciting and boosting saliency responses during testing without re-training. The proposed triple excitations can easily plug in different VSOD methods作者: 小教堂 時(shí)間: 2025-3-22 12:57
https://doi.org/10.1007/978-94-011-3068-4ifferent . based on only one input image. We further conduct experiments on Sky Time-lapse dataset, and the results demonstrate the superiority of our approach over the state-of-the-art methods for generating high-quality and dynamic videos, as well as the variety for generating videos with various 作者: 小教堂 時(shí)間: 2025-3-22 18:54 作者: 他日關(guān)稅重重 時(shí)間: 2025-3-22 23:01 作者: 吊胃口 時(shí)間: 2025-3-23 03:06 作者: Valves 時(shí)間: 2025-3-23 05:32 作者: 伸展 時(shí)間: 2025-3-23 09:52 作者: carotid-bruit 時(shí)間: 2025-3-23 17:36
TENet: Triple Excitation Network for Video Salient Object Detection,l and temporal features of VSOD. Furthermore, our semi-curriculum learning design enables the first online refinement strategy for VSOD, which allows exciting and boosting saliency responses during testing without re-training. The proposed triple excitations can easily plug in different VSOD methods作者: TRAWL 時(shí)間: 2025-3-23 20:34 作者: deciduous 時(shí)間: 2025-3-24 00:17
CLIFFNet for Monocular Depth Estimation with Hierarchical Embedding Loss,more reliable high-level cues. Through end-to-end training, CLIFFNet can learn to select the optimal combinations of low-level and high-level features, leading to more effective cross level feature fusion. When trained using the proposed hierarchical loss, CLIFFNet sets a new state of the art on pop作者: 多余 時(shí)間: 2025-3-24 06:00
Conference proceedings 2020g; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation..?..?.作者: Congeal 時(shí)間: 2025-3-24 08:37
0302-9743 processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation..?..?.978-3-030-58557-0978-3-030-58558-7Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 圖表證明 時(shí)間: 2025-3-24 13:25 作者: ALLAY 時(shí)間: 2025-3-24 15:27
Stream Regulation in Great Britain on four standard datasets and three backbones demonstrate that combining our centroid-based alignment loss results in absolute accuracy improvements of 4.4%, 1.2%, and 6.2% in 5-shot learning over the state of the art for object recognition, fine-grained classification, and cross-domain adaptation, respectively.作者: 階層 時(shí)間: 2025-3-24 22:06
The Effects of Light on the Breeding Seasonhigher accuracy when retrieving similar poses across different camera views, in comparison with 2D-to-3D pose lifting models. We also demonstrate the effectiveness of applying our embeddings to view-invariant action recognition and video alignment. Our code is available at ..作者: 原諒 時(shí)間: 2025-3-25 01:48
The Effects of Light on the Onset of Pubertyoving quantitative measures of both kinematic and dynamic plausibility. We demonstrate our method on character animation and pose estimation tasks on dynamic motions of dancing and sports with complex contact patterns.作者: Ischemic-Stroke 時(shí)間: 2025-3-25 05:42 作者: Jogging 時(shí)間: 2025-3-25 10:35
https://doi.org/10.1007/978-94-6209-221-1aluated on several motion estimation problems, including optical flow and rotational motion. As proof of concept, we also test our framework on 6-DOF estimation by performing the optimisation directly in 3D space.作者: STELL 時(shí)間: 2025-3-25 15:31 作者: 不愿 時(shí)間: 2025-3-25 19:39
D. Dudley Williams BSc, Dip. Ed MSc, PhDation, illumination estimation, as well as inverse kinematics. Comparing to traditional optimization-based methods, we can achieve comparable or better performance while being two to three orders of magnitude faster. Compared to deep learning-based approaches, our model consistently improves the performance on all metrics.作者: SMART 時(shí)間: 2025-3-25 22:01 作者: 壓艙物 時(shí)間: 2025-3-26 02:36
BLSM: A Bone-Level Skinned Model of the Human Mesh,L-type baseline. Our decoupled bone and shape representation also allows for out-of-box integration with standard graphics packages like Unity, facilitating full-body AR effects and image-driven character animation. Additional results and demos are available from the project webpage: ..作者: Coronary-Spasm 時(shí)間: 2025-3-26 07:33
Associative Alignment for Few-Shot Image Classification, on four standard datasets and three backbones demonstrate that combining our centroid-based alignment loss results in absolute accuracy improvements of 4.4%, 1.2%, and 6.2% in 5-shot learning over the state of the art for object recognition, fine-grained classification, and cross-domain adaptation, respectively.作者: 名義上 時(shí)間: 2025-3-26 10:40
View-Invariant Probabilistic Embedding for Human Pose,higher accuracy when retrieving similar poses across different camera views, in comparison with 2D-to-3D pose lifting models. We also demonstrate the effectiveness of applying our embeddings to view-invariant action recognition and video alignment. Our code is available at ..作者: inconceivable 時(shí)間: 2025-3-26 14:33
Contact and Human Dynamics from Monocular Video,oving quantitative measures of both kinematic and dynamic plausibility. We demonstrate our method on character animation and pose estimation tasks on dynamic motions of dancing and sports with complex contact patterns.作者: 駁船 時(shí)間: 2025-3-26 18:10
Few-Shot Scene-Adaptive Anomaly Detection, each target scene. We propose a meta-learning based approach for solving this new problem; extensive experimental results demonstrate the effectiveness of our proposed method. All codes are released in ..作者: fiction 時(shí)間: 2025-3-26 22:28
Entropy Minimisation Framework for Event-Based Vision Model Estimation,aluated on several motion estimation problems, including optical flow and rotational motion. As proof of concept, we also test our framework on 6-DOF estimation by performing the optimisation directly in 3D space.作者: Platelet 時(shí)間: 2025-3-27 01:41
Reconstructing NBA Players, any basketball pose and outputs a high resolution mesh and 3D pose for that player. We demonstrate substantial improvement over state-of-the-art, single-image methods for body shape reconstruction. Code and dataset are available at ..作者: BILL 時(shí)間: 2025-3-27 07:41
Deep Feedback Inverse Problem Solver,ation, illumination estimation, as well as inverse kinematics. Comparing to traditional optimization-based methods, we can achieve comparable or better performance while being two to three orders of magnitude faster. Compared to deep learning-based approaches, our model consistently improves the performance on all metrics.作者: 清楚 時(shí)間: 2025-3-27 10:14
Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-Tailed Classification, that the knowledge is adaptively transferred to the ‘Student’. We conduct extensive experiments and demonstrate that our method is able to achieve superior performances compared to state-of-the-art methods. We also show that our method can be easily plugged into state-of-the-art long-tailed classification algorithms for further improvements.作者: 暫時(shí)中止 時(shí)間: 2025-3-27 14:05
Conference proceedings 2020n, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic..The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with top作者: 控訴 時(shí)間: 2025-3-27 21:30 作者: Additive 時(shí)間: 2025-3-27 22:14 作者: Horizon 時(shí)間: 2025-3-28 04:23
Cyclic Functional Mapping: Self-supervised Correspondence Between Non-isometric Deformable Shapes,ate the point-wise descriptors apply in both directions, the network learns invariant structures without any labels while coping with non-isometric deformations. We show here state-of-the-art-results by a large margin for a variety of tasks compared to known self-supervised and supervised methods.作者: Override 時(shí)間: 2025-3-28 08:42 作者: 繞著哥哥問 時(shí)間: 2025-3-28 13:18
0302-9743 uter Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic..The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers dea作者: ELUC 時(shí)間: 2025-3-28 17:16 作者: 頭腦冷靜 時(shí)間: 2025-3-28 21:34 作者: dagger 時(shí)間: 2025-3-29 01:16
Cyclic Functional Mapping: Self-supervised Correspondence Between Non-isometric Deformable Shapes,k of alignment in non-Euclidean domains is one of the most fundamental and crucial problems in computer vision. As 3D scanners can generate highly complex and dense models, the mission of finding dense mappings between those models is vital. The novelty of our solution is based on a cyclic mapping b作者: hypotension 時(shí)間: 2025-3-29 05:48 作者: 愉快么 時(shí)間: 2025-3-29 08:18
Contact and Human Dynamics from Monocular Video,nstraints, such as feet penetrating the ground and bodies leaning at extreme angles. In this paper, we present a physics-based method for inferring 3D human motion from video sequences that takes initial 2D and 3D pose estimates as input. We first estimate ground contact timings with a novel predict作者: dura-mater 時(shí)間: 2025-3-29 15:03
PointPWC-Net: Cost Volume on Point Clouds for (Self-)Supervised Scene Flow Estimation,-to-fine fashion. Flow computed at the coarse level is upsampled and warped to a finer level, enabling the algorithm to accommodate for large motion without a prohibitive search space. We introduce novel cost volume, upsampling, and warping layers to efficiently handle 3D point cloud data. Unlike tr作者: 得罪 時(shí)間: 2025-3-29 19:25
Learning Implicit Surfaces from Point Clouds,ction) start to degrade in the presence of noisy and partial scans. Hence, deep learning based methods have recently been proposed to produce complete surfaces, even from partial scans. However, such data-driven methods struggle to generalize to new shapes with large geometric and topological variat作者: lymphoma 時(shí)間: 2025-3-29 22:08 作者: 不如樂死去 時(shí)間: 2025-3-30 03:06
Personalized Face Modeling for Improved Face Reconstruction and Motion Retargeting,d modeling capacity and fail to generalize well to in-the-wild data. Use of deformation transfer or multilinear tensor as a personalized 3DMM for blendshape interpolation does not address the fact that facial expressions result in different local and global skin deformations in different persons. Mo作者: acheon 時(shí)間: 2025-3-30 07:30 作者: 新字 時(shí)間: 2025-3-30 12:13 作者: CBC471 時(shí)間: 2025-3-30 13:18
PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments,proaches are mostly built on horizontal bounding box detectors by introducing an additional angle dimension optimized by a distance loss. However, as the distance loss only minimizes the angle error of the OBB and that it loosely correlates to the IoU, it is insensitive to objects with high aspect r作者: eardrum 時(shí)間: 2025-3-30 18:04
TENet: Triple Excitation Network for Video Salient Object Detection,n (VSOD) from three aspects, spatial, temporal, and online excitations. These excitation mechanisms are designed following the spirit of curriculum learning and aim to reduce learning ambiguities at the beginning of training by selectively exciting feature activations using ground truth. Then we gra作者: 歡笑 時(shí)間: 2025-3-30 22:51
Deep Feedback Inverse Problem Solver, the forward process and learn an iterative update model. Specifically, at each iteration, the neural network takes the feedback as input and outputs an update on current estimation. Our approach does not have any restrictions on the forward process; it does not require any prior knowledge either. T作者: 油膏 時(shí)間: 2025-3-31 02:45 作者: RODE 時(shí)間: 2025-3-31 07:30 作者: Pigeon 時(shí)間: 2025-3-31 10:51
DTVNet: Dynamic Time-Lapse Video Generation via Single Still Image,ingle landscape image, which are conditioned on normalized motion vectors. The proposed DTVNet consists of two submodules: . (OFE) and . (DVG). The OFE maps a sequence of optical flow maps to a . that encodes the motion information inside the generated video. The DVG contains motion and content stre作者: 跟隨 時(shí)間: 2025-3-31 15:03 作者: Custodian 時(shí)間: 2025-3-31 20:06 作者: agitate 時(shí)間: 2025-4-1 00:47
Stream Regulation in Great Britainiative alignment for leveraging part of the base data by aligning the novel training instances to the closely related ones in the base training set. This expands the size of the effective novel training set by adding extra “related base” instances to the few novel ones, thereby allowing a constructi作者: coagulate 時(shí)間: 2025-4-1 05:22 作者: ABIDE 時(shí)間: 2025-4-1 08:41
The Effects of Light on the Breeding Seasons to recognize similarity in human body poses across multiple views. This ability is useful for analyzing body movements and human behaviors in images and videos. In this paper, we propose an approach for learning a compact view-invariant embedding space from 2D joint keypoints alone, without explic作者: 詼諧 時(shí)間: 2025-4-1 11:36
The Effects of Light on the Onset of Pubertynstraints, such as feet penetrating the ground and bodies leaning at extreme angles. In this paper, we present a physics-based method for inferring 3D human motion from video sequences that takes initial 2D and 3D pose estimates as input. We first estimate ground contact timings with a novel predict作者: minimal 時(shí)間: 2025-4-1 15:46
The Effects of Light on the Onset of Puberty-to-fine fashion. Flow computed at the coarse level is upsampled and warped to a finer level, enabling the algorithm to accommodate for large motion without a prohibitive search space. We introduce novel cost volume, upsampling, and warping layers to efficiently handle 3D point cloud data. Unlike tr作者: 比目魚 時(shí)間: 2025-4-1 20:24
K. F. Walker,R. J. Shiel,P. L. Cadwalladerction) start to degrade in the presence of noisy and partial scans. Hence, deep learning based methods have recently been proposed to produce complete surfaces, even from partial scans. However, such data-driven methods struggle to generalize to new shapes with large geometric and topological variat
