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

預(yù)防注射

Sequential Convolution and Runge-Kutta Residual Architecture for Image Compressed Sensing,as a discrete dynamical system. Finally, the implementation of RK-CCSNet achieves state-of-the-art performance on influential benchmarks with respect to prestigious baselines, and all the codes are available at ..

尖

Deep Hough Transform for Semantic Line Detection,o spotting individual points in the parametric domain, making the post-processing steps, .non-maximal suppression, more efficient. Furthermore, our method makes it easy to extract contextual line features, that are critical to accurate line detection. Experimental results on a public dataset demonst

Peak-Bone-Mass

Structured Landmark Detection via Topology-Adapting Deep Graph Learning,te-of-the-art approaches across all studied datasets indicating the superior performance in both robustness and accuracy. Qualitative visualizations of the learned graph topologies demonstrate a physically plausible connectivity laying behind the landmarks.

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3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning,mpractical in many realistic applications..To address the above issues, this paper proposes a novel algorithm called RSC-Net, which consists of a Resolution-aware network, a Self-supervision loss, and a Contrastive learning scheme. The proposed network is able to learn the 3D body shape and pose acr

BILK

懦夫

The Econometrics of Demand Systemshus constraining the search only in the feasible domain. In addition, a differentiable Prob-1 regularizer is proposed to ensure learning with NAS is reasonable. A distribution reshaping training strategy is also used to make training more stable. BP-NAS sets new state of the arts on both classificat

審問

The Importance of Socioeconomic Variablesly coherent talking-head videos with natural head movements. Thoughtful experiments on several standard benchmarks demonstrate that our method achieves significantly better results than the state-of-the-art methods in both quantitative and qualitative comparisons. The code is available on ..

BAIL

The Econometrics of Demand Systemshe relative-pose in a prior distribution. In various applications, we demonstrate that our model can achieve comparable or even better results than pose/3D model-supervised learning-based novel view synthesis (NVS) methods with any number of input views.

CAGE

The Econometrics of Demand Systemsrnable pose backbone exploiting the topology of human body, and (ii) a coupler to provide joint spatio-temporal attention weights across a video. Experiments (Code/models: .) show that VPN outperforms the state-of-the-art results for action classification on a large scale human activity dataset: .,

下邊深陷

https://doi.org/10.1057/9780230626317evels, respectively. To evaluate the effectiveness, we train a single-stage anchor-free detector called Soft Anchor-Point Detector (SAPD). Experiments show that our concise SAPD pushes the envelope of speed/accuracy trade-off to a new level, outperforming recent state-of-the-art anchor-free and anch