Search Results for author: Tianyu Yang

Found 26 papers, 13 papers with code

Compress3D: a Compressed Latent Space for 3D Generation from a Single Image

no code implementations20 Mar 2024 BoWen Zhang, Tianyu Yang, Yu Li, Lei Zhang, Xi Zhao

In this paper, we present a triplane autoencoder, which encodes 3D models into a compact triplane latent space to effectively compress both the 3D geometry and texture information.

OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

1 code implementation16 Mar 2024 Zhe Kong, Yong Zhang, Tianyu Yang, Tao Wang, Kaihao Zhang, Bizhu Wu, GuanYing Chen, Wei Liu, Wenhan Luo

We also observe that the initiation denoising timestep for noise blending is the key to identity preservation and layout.

Denoising Text-to-Image Generation

Symbol as Points: Panoptic Symbol Spotting via Point-based Representation

1 code implementation19 Jan 2024 Wenlong Liu, Tianyu Yang, YuHan Wang, QiZhi Yu, Lei Zhang

Finally, we propose a KNN interpolation mechanism for the mask attention module of the spotting head to better handle primitive mask downsampling, which is primitive-level in contrast to pixel-level for the image.

Point Cloud Segmentation Vector Graphics

GPAvatar: Generalizable and Precise Head Avatar from Image(s)

1 code implementation18 Jan 2024 Xuangeng Chu, Yu Li, Ailing Zeng, Tianyu Yang, Lijian Lin, Yunfei Liu, Tatsuya Harada

Head avatar reconstruction, crucial for applications in virtual reality, online meetings, gaming, and film industries, has garnered substantial attention within the computer vision community.

Neural Rendering Novel View Synthesis

A Video is Worth 256 Bases: Spatial-Temporal Expectation-Maximization Inversion for Zero-Shot Video Editing

no code implementations10 Dec 2023 Maomao Li, Yu Li, Tianyu Yang, Yunfei Liu, Dongxu Yue, Zhihui Lin, Dong Xu

This paper presents a video inversion approach for zero-shot video editing, which aims to model the input video with low-rank representation during the inversion process.

Video Editing

Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts

no code implementations18 Oct 2023 Xinhua Cheng, Tianyu Yang, Jianan Wang, Yu Li, Lei Zhang, Jian Zhang, Li Yuan

Recent text-to-3D generation methods achieve impressive 3D content creation capacity thanks to the advances in image diffusion models and optimizing strategies.

Text to 3D

Scalable Video Object Segmentation with Simplified Framework

no code implementations ICCV 2023 Qiangqiang Wu, Tianyu Yang, Wei Wu, Antoni Chan

The current popular methods for video object segmentation (VOS) implement feature matching through several hand-crafted modules that separately perform feature extraction and matching.

Object Semantic Segmentation +2

Dior-CVAE: Pre-trained Language Models and Diffusion Priors for Variational Dialog Generation

1 code implementation24 May 2023 Tianyu Yang, Thy Thy Tran, Iryna Gurevych

These models also suffer from posterior collapse, i. e., the decoder tends to ignore latent variables and directly access information captured in the encoder through the cross-attention mechanism.

Open-Domain Dialog Response Generation

DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks

1 code implementation CVPR 2023 Qiangqiang Wu, Tianyu Yang, Ziquan Liu, Baoyuan Wu, Ying Shan, Antoni B. Chan

However, we find that this simple baseline heavily relies on spatial cues while ignoring temporal relations for frame reconstruction, thus leading to sub-optimal temporal matching representations for VOT and VOS.

 Ranked #1 on Visual Object Tracking on TrackingNet (AUC metric)

Semantic Segmentation Video Object Segmentation +2

Latent Video Diffusion Models for High-Fidelity Long Video Generation

1 code implementation23 Nov 2022 Yingqing He, Tianyu Yang, Yong Zhang, Ying Shan, Qifeng Chen

Diffusion models have shown remarkable results recently but require significant computational resources.

Denoising Image Generation +3

LocVTP: Video-Text Pre-training for Temporal Localization

1 code implementation21 Jul 2022 Meng Cao, Tianyu Yang, Junwu Weng, Can Zhang, Jue Wang, Yuexian Zou

To further enhance the temporal reasoning ability of the learned feature, we propose a context projection head and a temporal aware contrastive loss to perceive the contextual relationships.

Retrieval Temporal Localization +1

Unsupervised Pre-training for Temporal Action Localization Tasks

1 code implementation CVPR 2022 Can Zhang, Tianyu Yang, Junwu Weng, Meng Cao, Jue Wang, Yuexian Zou

These pre-trained models can be sub-optimal for temporal localization tasks due to the inherent discrepancy between video-level classification and clip-level localization.

Contrastive Learning Representation Learning +4

Semantic-Preserving Linguistic Steganography by Pivot Translation and Semantic-Aware Bins Coding

no code implementations8 Mar 2022 Tianyu Yang, Hanzhou Wu, Biao Yi, Guorui Feng, Xinpeng Zhang

In this paper, we propose a novel LS method to modify a given text by pivoting it between two different languages and embed secret data by applying a GLS-like information encoding strategy.

Language Modelling Linguistic steganography +2

Exploring Denoised Cross-Video Contrast for Weakly-Supervised Temporal Action Localization

no code implementations CVPR 2022 Jingjing Li, Tianyu Yang, Wei Ji, Jue Wang, Li Cheng

Inspired by recent success in unsupervised contrastive representation learning, we propose a novel denoised cross-video contrastive algorithm, aiming to enhance the feature discrimination ability of video snippets for accurate temporal action localization in the weakly-supervised setting.

Contrastive Learning Denoising +4

Motion-aware Contrastive Video Representation Learning via Foreground-background Merging

1 code implementation CVPR 2022 Shuangrui Ding, Maomao Li, Tianyu Yang, Rui Qian, Haohang Xu, Qingyi Chen, Jue Wang, Hongkai Xiong

To alleviate such bias, we propose \textbf{F}oreground-b\textbf{a}ckground \textbf{Me}rging (FAME) to deliberately compose the moving foreground region of the selected video onto the static background of others.

Action Recognition Contrastive Learning +1

VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples

1 code implementation CVPR 2021 Tian Pan, Yibing Song, Tianyu Yang, Wenhao Jiang, Wei Liu

By empowering the temporal robustness of the encoder and modeling the temporal decay of the keys, our VideoMoCo improves MoCo temporally based on contrastive learning.

Action Recognition Contrastive Learning +1

ROAM: Recurrently Optimizing Tracking Model

no code implementations CVPR 2020 Tianyu Yang, Pengfei Xu, Runbo Hu, Hua Chai, Antoni B. Chan

In this paper, we design a tracking model consisting of response generation and bounding box regression, where the first component produces a heat map to indicate the presence of the object at different positions and the second part regresses the relative bounding box shifts to anchors mounted on sliding-window locations.

Meta-Learning Response Generation

Visual Tracking via Dynamic Memory Networks

no code implementations12 Jul 2019 Tianyu Yang, Antoni B. Chan

The reading and writing process of the external memory is controlled by an LSTM network with the search feature map as input.

Template Matching Visual Tracking

Generative adversarial network based on chaotic time series

no code implementations24 May 2019 Makoto Naruse, Takashi Matsubara, Nicolas Chauvet, Kazutaka Kanno, Tianyu Yang, Atsushi Uchida

Here we utilize chaotic time series generated experimentally by semiconductor lasers for the latent variables of GAN whereby the inherent nature of chaos can be reflected or transformed into the generated output data.

Generative Adversarial Network Time Series +1

Learning Dynamic Memory Networks for Object Tracking

1 code implementation ECCV 2018 Tianyu Yang, Antoni B. Chan

In this paper, we propose a dynamic memory network to adapt the template to the target's appearance variations during tracking.

Object Object Tracking +2

Recurrent Filter Learning for Visual Tracking

1 code implementation13 Aug 2017 Tianyu Yang, Antoni B. Chan

Recently using convolutional neural networks (CNNs) has gained popularity in visual tracking, due to its robust feature representation of images.

Object Visual Tracking

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