Search Results for author: Shiqi Yang

Found 30 papers, 13 papers with code

InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration

no code implementations4 Feb 2025 Senmao Li, Kai Wang, Joost Van de Weijer, Fahad Shahbaz Khan, Chun-Le Guo, Shiqi Yang, Yaxing Wang, Jian Yang, Ming-Ming Cheng

Diffusion priors have been used for blind face restoration (BFR) by fine-tuning diffusion models (DMs) on restoration datasets to recover low-quality images.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt

1 code implementation23 Jan 2025 Tao Liu, Kai Wang, Senmao Li, Joost Van de Weijer, Fahad Shahbaz Khan, Shiqi Yang, Yaxing Wang, Jian Yang, Ming-Ming Cheng

Drawing inspiration from the inherent context consistency, we propose a novel training-free method for consistent text-to-image (T2I) generation, termed "One-Prompt-One-Story" (1Prompt1Story).

Story Generation Text-to-Image Generation

Mobile-TeleVision: Predictive Motion Priors for Humanoid Whole-Body Control

no code implementations10 Dec 2024 Chenhao Lu, Xuxin Cheng, Jialong Li, Shiqi Yang, Mazeyu Ji, Chengjing Yuan, Ge Yang, Sha Yi, Xiaolong Wang

The locomotion policy is trained conditioned on this upper-body motion representation, ensuring that the system remains robust with both manipulation and locomotion.

motion retargeting Reinforcement Learning (RL)

OpenMU: Your Swiss Army Knife for Music Understanding

2 code implementations21 Oct 2024 Mengjie Zhao, Zhi Zhong, Zhuoyuan Mao, Shiqi Yang, Wei-Hsiang Liao, Shusuke Takahashi, Hiromi Wakaki, Yuki Mitsufuji

We present OpenMU-Bench, a large-scale benchmark suite for addressing the data scarcity issue in training multimodal language models to understand music.

GLOV: Guided Large Language Models as Implicit Optimizers for Vision Language Models

1 code implementation8 Oct 2024 M. Jehanzeb Mirza, Mengjie Zhao, Zhuoyuan Mao, Sivan Doveh, Wei Lin, Paul Gavrikov, Michael Dorkenwald, Shiqi Yang, Saurav Jha, Hiromi Wakaki, Yuki Mitsufuji, Horst Possegger, Rogerio Feris, Leonid Karlinsky, James Glass

In each respective optimization step, the ranked prompts are fed as in-context examples (with their accuracies) to equip the LLM with the knowledge of the type of text prompts preferred by the downstream VLM.

Zero-Shot Learning

Mining Your Own Secrets: Diffusion Classifier Scores for Continual Personalization of Text-to-Image Diffusion Models

no code implementations1 Oct 2024 Saurav Jha, Shiqi Yang, Masato Ishii, Mengjie Zhao, Christian Simon, Muhammad Jehanzeb Mirza, Dong Gong, Lina Yao, Shusuke Takahashi, Yuki Mitsufuji

Personalized text-to-image diffusion models have grown popular for their ability to efficiently acquire a new concept from user-defined text descriptions and a few images.

Continual Learning

ACE: A Cross-Platform Visual-Exoskeletons System for Low-Cost Dexterous Teleoperation

no code implementations21 Aug 2024 Shiqi Yang, Minghuan Liu, Yuzhe Qin, Runyu Ding, Jialong Li, Xuxin Cheng, Ruihan Yang, Sha Yi, Xiaolong Wang

Compared to previous systems, which often require hardware customization according to different robots, our single system can generalize to humanoid hands, arm-hands, arm-gripper, and quadruped-gripper systems with high-precision teleoperation.

Imitation Learning

Bunny-VisionPro: Real-Time Bimanual Dexterous Teleoperation for Imitation Learning

no code implementations3 Jul 2024 Runyu Ding, Yuzhe Qin, Jiyue Zhu, Chengzhe Jia, Shiqi Yang, Ruihan Yang, Xiaojuan Qi, Xiaolong Wang

Our system's ability to handle bimanual manipulations while prioritizing safety and real-time performance makes it a powerful tool for advancing dexterous manipulation and imitation learning.

Imitation Learning

Open-TeleVision: Teleoperation with Immersive Active Visual Feedback

no code implementations1 Jul 2024 Xuxin Cheng, Jialong Li, Shiqi Yang, Ge Yang, Xiaolong Wang

Teleoperation serves as a powerful method for collecting on-robot data essential for robot learning from demonstrations.

Imitation Learning

DestripeCycleGAN: Stripe Simulation CycleGAN for Unsupervised Infrared Image Destriping

no code implementations14 Feb 2024 Shiqi Yang, Hanlin Qin, Shuai Yuan, Xiang Yan, Hossein Rahmani

However, when applied to the infrared destriping task, it becomes challenging for the vanilla auxiliary generator to consistently produce vertical noise under unsupervised constraints.

Denoising Image Restoration

Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference

1 code implementation15 Dec 2023 Senmao Li, Taihang Hu, Joost Van de Weijer, Fahad Shahbaz Khan, Tao Liu, Linxuan Li, Shiqi Yang, Yaxing Wang, Ming-Ming Cheng, Jian Yang

This insight motivates us to omit encoder computation at certain adjacent time-steps and reuse encoder features of previous time-steps as input to the decoder in multiple time-steps.

Decoder Denoising +2

MaTe3D: Mask-guided Text-based 3D-aware Portrait Editing

1 code implementation12 Dec 2023 Kangneng Zhou, Daiheng Gao, Xuan Wang, Jie Zhang, Peng Zhang, Xusen Sun, Longhao Zhang, Shiqi Yang, Bang Zhang, Liefeng Bo, Yaxing Wang, Ming-Ming Cheng

This enhances masked-based editing in local areas; second, we present a novel distillation strategy: Conditional Distillation on Geometry and Texture (CDGT).

Alleviating Behavior Data Imbalance for Multi-Behavior Graph Collaborative Filtering

no code implementations12 Nov 2023 Yijie Zhang, Yuanchen Bei, Shiqi Yang, Hao Chen, Zhiqing Li, Lijia Chen, Feiran Huang

To this end, we propose IMGCF, a simple but effective model to alleviate behavior data imbalance for multi-behavior graph collaborative filtering.

Collaborative Filtering Multi-Task Learning +1

Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing

1 code implementation NeurIPS 2023 Kai Wang, Fei Yang, Shiqi Yang, Muhammad Atif Butt, Joost Van de Weijer

Large-scale text-to-image generative models have been a ground-breaking development in generative AI, with diffusion models showing their astounding ability to synthesize convincing images following an input text prompt.

Text-based Image Editing

Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering

no code implementations1 Sep 2023 Shiqi Yang, Yaxing Wang, Joost Van de Weijer, Luis Herranz, Shangling Jui, Jian Yang

We capture this intrinsic structure by defining local affinity of the target data, and encourage label consistency among data with high local affinity.

Clustering Source-Free Domain Adaptation

A Critical Look at the Current Usage of Foundation Model for Dense Recognition Task

no code implementations6 Jul 2023 Shiqi Yang, Atsushi Hashimoto, Yoshitaka Ushiku

In recent years large model trained on huge amount of cross-modality data, which is usually be termed as foundation model, achieves conspicuous accomplishment in many fields, such as image recognition and generation.

Segmentation

OneRing: A Simple Method for Source-free Open-partial Domain Adaptation

1 code implementation7 Jun 2022 Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost Van de Weijer

In this paper, we investigate Source-free Open-partial Domain Adaptation (SF-OPDA), which addresses the situation where there exist both domain and category shifts between source and target domains.

Domain Generalization Open Set Learning +2

Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation

1 code implementation9 May 2022 Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost Van de Weijer

Treating SFDA as an unsupervised clustering problem and following the intuition that local neighbors in feature space should have more similar predictions than other features, we propose to optimize an objective of prediction consistency.

Clustering Diversity +1

Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation

2 code implementations NeurIPS 2021 Shiqi Yang, Yaxing Wang, Joost Van de Weijer, Luis Herranz, Shangling Jui

In this paper, we address the challenging source-free domain adaptation (SFDA) problem, where the source pretrained model is adapted to the target domain in the absence of source data.

Source-Free Domain Adaptation

Generalized Source-free Domain Adaptation

1 code implementation ICCV 2021 Shiqi Yang, Yaxing Wang, Joost Van de Weijer, Luis Herranz, Shangling Jui

In this paper, we propose a new domain adaptation paradigm called Generalized Source-free Domain Adaptation (G-SFDA), where the learned model needs to perform well on both the target and source domains, with only access to current unlabeled target data during adaptation.

Source-Free Domain Adaptation

On Implicit Attribute Localization for Generalized Zero-Shot Learning

no code implementations8 Mar 2021 Shiqi Yang, Kai Wang, Luis Herranz, Joost Van de Weijer

Zero-shot learning (ZSL) aims to discriminate images from unseen classes by exploiting relations to seen classes via their attribute-based descriptions.

Attribute Generalized Zero-Shot Learning

Casting a BAIT for Offline and Online Source-free Domain Adaptation

2 code implementations23 Oct 2020 Shiqi Yang, Yaxing Wang, Joost Van de Weijer, Luis Herranz, Shangling Jui

When adapting to the target domain, the additional classifier initialized from source classifier is expected to find misclassified features.

Source-Free Domain Adaptation Unsupervised Domain Adaptation

Odd-even layer-number effect and layer-dependent magnetic phase diagrams in MnBi2Te4

no code implementations12 Jun 2020 Shiqi Yang, Xiaolong Xu, Yaozheng Zhu, Ruirui Niu, Chunqiang Xu, Yuxuan Peng, Xing Cheng, Xionghui Jia, Xiaofeng Xu, Jianming Lu, Yu Ye

However, the layer-dependent magnetism of MnBi2Te4, which is fundamental and crucial for further exploration of quantum phenomena in this system, remains elusive.

Materials Science

Simple and effective localized attribute representations for zero-shot learning

no code implementations10 Jun 2020 Shiqi Yang, Kai Wang, Luis Herranz, Joost Van de Weijer

Zero-shot learning (ZSL) aims to discriminate images from unseen classes by exploiting relations to seen classes via their semantic descriptions.

Attribute Zero-Shot Learning

Attention to Refine through Multi-Scales for Semantic Segmentation

no code implementations9 Jul 2018 Shiqi Yang, Gang Peng

This paper proposes a novel attention model for semantic segmentation, which aggregates multi-scale and context features to refine prediction.

Semantic Segmentation

Parallel Convolutional Networks for Image Recognition via a Discriminator

no code implementations6 Jul 2018 Shiqi Yang, Gang Peng

The discriminator is core which drives parallel networks to focus on different regions and learn different representations.

D-PCN: Parallel Convolutional Networks for Image Recognition via a Discriminator

no code implementations12 Nov 2017 Shiqi Yang, Gang Peng

The discriminator is core which drives parallel networks to focus on different regions and learn complementary representations.

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