Search Results for author: Ping Hu

Found 14 papers, 4 papers with code

Many-to-many Splatting for Efficient Video Frame Interpolation

1 code implementation7 Apr 2022 Ping Hu, Simon Niklaus, Stan Sclaroff, Kate Saenko

Motion-based video frame interpolation commonly relies on optical flow to warp pixels from the inputs to the desired interpolation instant.

Frame Motion Estimation +2

Optimal Aggregation Strategies for Social Learning over Graphs

no code implementations14 Mar 2022 Ping Hu, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed

Adaptive social learning is a useful tool for studying distributed decision-making problems over graphs.

Decision Making

Splatting-based Synthesis for Video Frame Interpolation

no code implementations25 Jan 2022 Simon Niklaus, Ping Hu, Jiawen Chen

Specifically, splatting can be used to warp the input images to an arbitrary temporal location based on an optical flow estimate.

Frame Optical Flow Estimation +1

Learning to Detect Every Thing in an Open World

no code implementations3 Dec 2021 Kuniaki Saito, Ping Hu, Trevor Darrell, Kate Saenko

LDET leads to significant improvements on many datasets in the open-world instance segmentation task, outperforming baselines on cross-category generalization on COCO, as well as cross-dataset evaluation on UVO and Cityscapes.

Data Augmentation Instance Segmentation +2

Conterfactual Generative Zero-Shot Semantic Segmentation

no code implementations11 Jun 2021 Feihong Shen, Jun Liu, Ping Hu

In this work, we consider counterfactual methods to avoid the confounder in the original model.

Causal Inference Semantic Segmentation +1

ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes

1 code implementation4 Jun 2021 Dina Bashkirova, Mohamed Abdelfattah, Ziliang Zhu, James Akl, Fadi Alladkani, Ping Hu, Vitaly Ablavsky, Berk Calli, Sarah Adel Bargal, Kate Saenko

Recyclable waste detection poses a unique computer vision challenge as it requires detection of highly deformable and often translucent objects in cluttered scenes without the kind of context information usually present in human-centric datasets.

Object Detection Self-Supervised Learning +2

Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation

no code implementations NeurIPS 2020 Ping Hu, Stan Sclaroff, Kate Saenko

Recently, most ZSS methods focus on learning the visual-semantic correspondence to transfer knowledge from seen classes to unseen classes at the pixel level.

Semantic correspondence Semantic Segmentation

Real-time Semantic Segmentation with Fast Attention

1 code implementation7 Jul 2020 Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko, Stan Sclaroff

The proposed architecture relies on our fast spatial attention, which is a simple yet efficient modification of the popular self-attention mechanism and captures the same rich spatial context at a small fraction of the computational cost, by changing the order of operations.

Real-Time Semantic Segmentation

Motion-Guided Cascaded Refinement Network for Video Object Segmentation

no code implementations CVPR 2018 Ping Hu, Gang Wang, Xiangfei Kong, Jason Kuen, Yap-Peng Tan

Then, the proposed Cascaded Refinement Network(CRN) takes the coarse segmentation as guidance to generate an accurate segmentation of full resolution.

Frame Optical Flow Estimation +3

Deep Level Sets for Salient Object Detection

no code implementations CVPR 2017 Ping Hu, Bing Shuai, Jun Liu, Gang Wang

Our method drives the network to learn a Level Set function for salient objects so it can output more accurate boundaries and compact saliency.

RGB Salient Object Detection Saliency Detection +1

Global Context-Aware Attention LSTM Networks for 3D Action Recognition

no code implementations CVPR 2017 Jun Liu, Gang Wang, Ping Hu, Ling-Yu Duan, Alex C. Kot

Hence we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for 3D action recognition, which is able to selectively focus on the informative joints in the action sequence with the assistance of global contextual information.

Action Analysis Frame +2

Tilings in graphons

no code implementations9 Jun 2016 Jan Hladky, Ping Hu, Diana Piguet

We introduce a counterpart to the notion of vertex disjoint tilings by copy of a fixed graph F to the setting of graphons.

Combinatorics

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