Search Results for author: Ping Hu

Found 20 papers, 5 papers with code

Diffusion-based Image Translation with Label Guidance for Domain Adaptive Semantic Segmentation

no code implementations ICCV 2023 Duo Peng, Ping Hu, Qiuhong Ke, Jun Liu

Translating images from a source domain to a target domain for learning target models is one of the most common strategies in domain adaptive semantic segmentation (DASS).

Denoising Semantic Segmentation +1

DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition with Limited Annotations

no code implementations3 Aug 2023 Ping Hu, Ximeng Sun, Stan Sclaroff, Kate Saenko

Previous works have focused on learning the alignment between textual and visual spaces to compensate for limited image labels, yet may suffer from reduced accuracy due to the scarcity of high-quality multi-label annotations.

Non-Asymptotic Performance of Social Machine Learning Under Limited Data

no code implementations15 Jun 2023 Ping Hu, Virginia Bordignon, Mert Kayaalp, Ali H. Sayed

This paper studies the probability of error associated with the social machine learning framework, which involves an independent training phase followed by a cooperative decision-making phase over a graph.

Classification Decision Making

Token Boosting for Robust Self-Supervised Visual Transformer Pre-training

no code implementations CVPR 2023 Tianjiao Li, Lin Geng Foo, Ping Hu, Xindi Shang, Hossein Rahmani, Zehuan Yuan, Jun Liu

Pre-training VTs on such corrupted data can be challenging, especially when we pre-train via the masked autoencoding approach, where both the inputs and masked ``ground truth" targets can potentially be unreliable in this case.

GAIT: Generating Aesthetic Indoor Tours with Deep Reinforcement Learning

no code implementations ICCV 2023 Desai Xie, Ping Hu, Xin Sun, Soren Pirk, Jianming Zhang, Radomir Mech, Arie E. Kaufman

Placing and orienting a camera to compose aesthetically meaningful shots of a scene is not only a key objective in real-world photography and cinematography but also for virtual content creation.

Mixed Reality reinforcement-learning

Many-to-many Splatting for Efficient Video Frame Interpolation

1 code implementation CVPR 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.

Motion Estimation Optical Flow Estimation +1

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

Frame interpolation is an essential video processing technique that adjusts the temporal resolution of an image sequence.

Optical Flow Estimation Video Frame Interpolation

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 +3

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 +2

ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes

1 code implementation CVPR 2022 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 Object Detection +3

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 +1

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.

Optical Flow Estimation Semantic Segmentation +2

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 One-Shot 3D Action Recognition +1

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.

object-detection RGB Salient Object Detection +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.


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