Titlebook: Computer Vision – ECCV 2020; 16th European Confer Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm Conference proceedings 2020 Springer Natur

PRISE

Fair Knapsack Pricing for Data Marketplacesostic prediction distribution. In contrast to previous methods, our representation allows us to define a joint probabilistic learning objective that minimizes the dissimilarity between the two distributions. Our approach achieves state of the art results on the PASCAL VOC 2012 data set, outperforming the best baseline by . and ..

addition

Toward Fine-Grained Facial Expression Manipulation,uilt on U-Net but strengthened by multi-scale feature fusion (MSF) mechanism for high-quality expression editing purposes. Extensive experiments on both quantitative and qualitative evaluation demonstrate the improvements of our proposed approach compared to the state-of-the-art expression editing methods. Code is available at ..

纵火

Adaptive Object Detection with Dual Multi-label Prediction,mation to ensure consistent object category discoveries between the object recognition task and the object detection task. Experiments are conducted on a few benchmark datasets and the results show the proposed model outperforms the state-of-the-art comparison methods.

HEDGE

Novel View Synthesis on Unpaired Data by Conditional Deformable Variational Auto-Encoder,es the code drawn from it to synthesize the reconstructed and the view-translated images. To further ensure the disentanglement between the views and other factors, we add adversarial training on the code. The results and ablation studies on MultiPIE and 3D chair datasets validate the effectiveness of the framework in cVAE and the designed module.

坚毅

Improving Knowledge Distillation via Category Structure,re from the teacher to the student supplements category-level structured relations for training a better student. Extensive experiments show that our method groups samples from the same category tighter in the embedding space and the superiority of our method in comparison with closely related works are validated in different datasets and models.

reception

Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances,ostic prediction distribution. In contrast to previous methods, our representation allows us to define a joint probabilistic learning objective that minimizes the dissimilarity between the two distributions. Our approach achieves state of the art results on the PASCAL VOC 2012 data set, outperforming the best baseline by . and ..

极力证明

Marcelo F. Frias,Silvia E. Gordilloof the advances made in prior settings as well as single-modality baselines. While some transfer, we find significantly lower absolute performance in the continuous setting – suggesting that performance in prior ‘navigation-graph’ settings may be inflated by the strong implicit assumptions. Code at ..

奇思怪想

用不完

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

ostensible

SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation, of element-wise multiplications, im2col, and standard convolution. It is a general framework such that several previous methods can be seen as special cases of SAC. Using SAC, we build SqueezeSegV3 for LiDAR point-cloud segmentation and outperform all previous published methods by at least 2.0% mIo