no code implementations • 7 May 2024 • Yongming Zhang, Tianyu Zhang, Haoran Xie
In this work, we propose TexControl, a sketch-based fashion generation framework that uses a two-stage pipeline to generate the fashion image corresponding to the sketch input.
no code implementations • 12 Apr 2024 • Tianyu Zhang, Zixuan Zhao, Jiaqi Huang, Jingyu Hua, Sheng Zhong
As Large Language Models (LLMs) of Prompt Jailbreaking are getting more and more attention, it is of great significance to raise a generalized research paradigm to evaluate attack strengths and a basic model to conduct subtler experiments.
no code implementations • 9 Apr 2024 • Xingwei Qu, Yuelin Bai, Yinghao Ma, Ziya Zhou, Ka Man Lo, Jiaheng Liu, Ruibin Yuan, Lejun Min, Xueling Liu, Tianyu Zhang, Xinrun Du, Shuyue Guo, Yiming Liang, Yizhi Li, Shangda Wu, Junting Zhou, Tianyu Zheng, Ziyang Ma, Fengze Han, Wei Xue, Gus Xia, Emmanouil Benetos, Xiang Yue, Chenghua Lin, Xu Tan, Stephen W. Huang, Wenhu Chen, Jie Fu, Ge Zhang
In this paper, we explore the application of Large Language Models (LLMs) to the pre-training of music.
2 code implementations • 5 Apr 2024 • Wenyi Mo, Tianyu Zhang, Yalong Bai, Bing Su, Ji-Rong Wen, Qing Yang
Users assign weights or alter the injection time steps of certain words in the text prompts to improve the quality of generated images.
no code implementations • 30 Mar 2024 • Chengyuan Li, Tianyu Zhang, Xusheng Du, Ye Zhang, Haoran Xie
This paper explores the extensive applications of generative AI technologies in architectural design, a trend that has benefited from the rapid development of deep generative models.
1 code implementation • 26 Feb 2024 • Tianyu Zhang, Chengbin Hou, Rui Jiang, Xuegong Zhang, Chenghu Zhou, Ke Tang, Hairong Lv
Considering the NIE problem, LICAP adopts a novel sampling strategy called top nodes preferred hierarchical sampling to first group all interested nodes into a top bin and a non-top bin based on node importance scores, and then divide the nodes within top bin into several finer bins also based on the scores.
1 code implementation • 17 Jan 2024 • Luyi Han, Tao Tan, Tianyu Zhang, Yuan Gao, Xin Wang, Valentina Longo, Sofía Ventura-Díaz, Anna D'Angelo, Jonas Teuwen, Ritse Mann
We use a clinical dataset with 1630 MRI scans from 314 patients treated with NAC.
no code implementations • 11 Jan 2024 • Bin Dou, Tianyu Zhang, Yongjia Ma, Zhaohui Wang, Zejian yuan
We propose Compact and Swift Segmenting 3D Gaussians(CoSSegGaussians), a method for compact 3D-consistent scene segmentation at fast rendering speed with only RGB images input.
no code implementations • 18 Oct 2023 • Tianyu Zhang, Jing Lei
We propose a weighted rolling-validation procedure, an online variant of leave-one-out cross-validation, that costs minimal extra computation for many typical stochastic gradient descent estimators.
1 code implementation • 4 Oct 2023 • Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
Generative flow networks (GFlowNets) are sequential sampling models trained to match a given distribution.
no code implementations • 10 Jul 2023 • Yoshua Bengio, Prateek Gupta, Lu Li, Soham Phade, Sunil Srinivasa, Andrew Williams, Tianyu Zhang, Yang Zhang, Stephan Zheng
On the other hand, an interdisciplinary panel of human experts in law, policy, sociology, economics and environmental science, evaluated the solutions qualitatively.
no code implementations • 6 Jul 2023 • Xin Wang, Tao Tan, Yuan Gao, Luyi Han, Tianyu Zhang, Chunyao Lu, Regina Beets-Tan, Ruisheng Su, Ritse Mann
The question of 'what the symmetrical Bi-MG would look like when the asymmetrical abnormalities have been removed ?'
1 code implementation • 3 Jul 2023 • Luyi Han, Tianyu Zhang, Yunzhi Huang, Haoran Dou, Xin Wang, Yuan Gao, Chunyao Lu, Tan Tao, Ritse Mann
Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons.
1 code implementation • 3 Jul 2023 • Tianyu Zhang, Luyi Han, Anna D'Angelo, Xin Wang, Yuan Gao, Chunyao Lu, Jonas Teuwen, Regina Beets-Tan, Tao Tan, Ritse Mann
DWIs with different b-values are fused to efficiently utilize the difference features of DWIs.
no code implementations • 17 Apr 2023 • Jinpeng Liao, Tianyu Zhang, Yilong Zhang, Chunhui Li, Zhihong Huang
In comparison to OCTA images obtained via the SV-OCTA (PSNR: 17. 809) and ED-OCTA (PSNR: 18. 049) using four-repeated OCT scans, OCTA images extracted by VET exhibit moderate quality (PSNR: 17. 515) and higher image contrast while reducing the required data acquisition time from ~8 s to ~2 s. Based on visual observations, the proposed VET outperforms SV and ED algorithms when using neck and face OCTA data in areas that are challenging to scan.
1 code implementation • 15 Feb 2023 • Kam Woh Ng, Xiatian Zhu, Jiun Tian Hoe, Chee Seng Chan, Tianyu Zhang, Yi-Zhe Song, Tao Xiang
However, these methods often overlook the fact that the similarity between data points in the continuous feature space may not be preserved in the discrete hash code space, due to the limited similarity range of hash codes.
1 code implementation • 3 Feb 2023 • Tianyu Zhang, Tao Tan, Luyi Han, Xin Wang, Yuan Gao, Jonas Teuwen, Regina Beets-Tan, Ritse Mann
Then the multi-parameter fusion with attention module enables the interaction of the encoded information from different parameters through a set of algorithmic strategies, and applies different weights to the information through the attention mechanism after information fusion to obtain refined representation information.
1 code implementation • 1 Feb 2023 • Luyi Han, Tao Tan, Tianyu Zhang, Yunzhi Huang, Xin Wang, Yuan Gao, Jonas Teuwen, Ritse Mann
Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences.
no code implementations • 6 Jan 2023 • Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry
To integrate high amounts of renewable energy resources, electrical power grids must be able to cope with high amplitude, fast timescale variations in power generation.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • CVPR 2023 • Guiwei Zhang, Yongfei Zhang, Tianyu Zhang, Bo Li, ShiLiang Pu
Although recent studies empirically show that injecting Convolutional Neural Networks (CNNs) into Vision Transformers (ViTs) can improve the performance of person re-identification, the rationale behind it remains elusive.
1 code implementation • 30 Nov 2022 • Tianyu Zhang, Xusheng Du, Chia-Ming Chang, Xi Yang, Haoran Xie
However, it is difficult to draw a proper scene graph for image retrieval, image generation, and multi-modal applications.
no code implementations • 4 Sep 2022 • Suraj Mishra, Yizhe Zhang, Li Zhang, Tianyu Zhang, X. Sharon Hu, Danny Z. Chen
Specifically, we analyze the convolutional network's behavior (field-of-view) to find the location of deep supervision for improved feature extraction.
2 code implementations • 15 Aug 2022 • Tianyu Zhang, Andrew Williams, Soham Phade, Sunil Srinivasa, Yang Zhang, Prateek Gupta, Yoshua Bengio, Stephan Zheng
To facilitate this research, here we introduce RICE-N, a multi-region integrated assessment model that simulates the global climate and economy, and which can be used to design and evaluate the strategic outcomes for different negotiation and agreement frameworks.
no code implementations • 14 Jun 2022 • Tianyu Zhang, Amin Banitalebi-Dehkordi, Yong Zhang
We propose a new approach for solving the data labeling and inference latency issues in combinatorial optimization based on the use of the reinforcement learning (RL) paradigm.
1 code implementation • 2 Mar 2022 • Moksh Jain, Emmanuel Bengio, Alex-Hernandez Garcia, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Micheal Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
In this work, we propose an active learning algorithm leveraging epistemic uncertainty estimation and the recently proposed GFlowNets as a generator of diverse candidate solutions, with the objective to obtain a diverse batch of useful (as defined by some utility function, for example, the predicted anti-microbial activity of a peptide) and informative candidates after each round.
1 code implementation • 27 Nov 2021 • Yang Lin, Tianyu Zhang, Peiqin Sun, Zheng Li, Shuchang Zhou
Network quantization significantly reduces model inference complexity and has been widely used in real-world deployments.
Ranked #1 on Quantization on ImageNet
1 code implementation • 5 Nov 2021 • Tianyu Zhang, Yuxiang Ren, Wenzheng Feng, Weitao Du, Xuecang Zhang
In this paper, we show the potential hazards of inappropriate augmentations and then propose a novel Collaborative Graph Contrastive Learning framework (CGCL).
2 code implementations • ICLR 2022 • Victor Schmidt, Alexandra Sasha Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud, Sunand Raghupathi, Gautier Cosne, Adrien Juraver, Vahe Vardanyan, Alex Hernandez-Garcia, Yoshua Bengio
Climate change is a major threat to humanity, and the actions required to prevent its catastrophic consequences include changes in both policy-making and individual behaviour.
2 code implementations • NeurIPS 2021 • Jiun Tian Hoe, Kam Woh Ng, Tianyu Zhang, Chee Seng Chan, Yi-Zhe Song, Tao Xiang
In this work, we propose a novel deep hashing model with only a single learning objective.
no code implementations • 5 May 2021 • Yunhua Xiang, Tianyu Zhang, Xu Wang, Ali Shojaie, Noah Simon
Originally developed for imputing missing entries in low rank, or approximately low rank matrices, matrix completion has proven widely effective in many problems where there is no reason to assume low-dimensional linear structure in the underlying matrix, as would be imposed by rank constraints.
no code implementations • 30 Mar 2021 • Tianyu Zhang, Longhui Wei, Lingxi Xie, Zijie Zhuang, Yongfei Zhang, Bo Li, Qi Tian
Recently, the Transformer module has been transplanted from natural language processing to computer vision.
no code implementations • 16 Mar 2021 • Chang Liu, Lixin Fan, Kam Woh Ng, Yilun Jin, Ce Ju, Tianyu Zhang, Chee Seng Chan, Qiang Yang
This paper proposes a novel ternary hash encoding for learning to hash methods, which provides a principled more efficient coding scheme with performances better than those of the state-of-the-art binary hashing counterparts.
no code implementations • 1 Jan 2021 • Jun Yan, Mrigank Raman, Tianyu Zhang, Ryan Rossi, Handong Zhao, Sungchul Kim, Nedim Lipka, Xiang Ren
Recently, neural-symbolic architectures have achieved success on commonsense reasoning through effectively encoding relational structures retrieved from external knowledge graphs (KGs) and obtained state-of-the-art results in tasks such as (commonsense) question answering and natural language inference.
1 code implementation • CVPR 2021 • Tianyu Zhang, Lingxi Xie, Longhui Wei, Zijie Zhuang, Yongfei Zhang, Bo Li, Qi Tian
The main difficulty of person re-identification (ReID) lies in collecting annotated data and transferring the model across different domains.
no code implementations • 16 Nov 2020 • Florent Pled, Christophe Desceliers, Tianyu Zhang
An initial database made up with input and target data is first generated from the computational model, from which a processed database is deduced by conditioning the input data with respect to the target data using the nonparametric statistics.
1 code implementation • Findings (ACL) 2021 • Jun Yan, Mrigank Raman, Aaron Chan, Tianyu Zhang, Ryan Rossi, Handong Zhao, Sungchul Kim, Nedim Lipka, Xiang Ren
Recently, knowledge graph (KG) augmented models have achieved noteworthy success on various commonsense reasoning tasks.
no code implementations • 20 Jun 2020 • Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang
This paper investigates capabilities of Privacy-Preserving Deep Learning (PPDL) mechanisms against various forms of privacy attacks.
1 code implementation • ECCV 2020 • Zijie Zhuang, Longhui Wei, Lingxi Xie, Tianyu Zhang, Hengheng Zhang, Haozhe Wu, Haizhou Ai, Qi Tian
The fundamental difficulty in person re-identification (ReID) lies in learning the correspondence among individual cameras.
Ranked #16 on Unsupervised Domain Adaptation on Duke to Market
Direct Transfer Person Re-identification Domain Adaptive Person Re-Identification +2
no code implementations • 18 Dec 2019 • Tianyu Zhang, Lei Zhu, Qian Zhao, Kilho Shin
Quantization of weights of deep neural networks (DNN) has proven to be an effective solution for the purpose of implementing DNNs on edge devices such as mobiles, ASICs and FPGAs, because they have no sufficient resources to support computation involving millions of high precision weights and multiply-accumulate operations.
no code implementations • 15 Oct 2019 • Mingjie Wu, Yongfei Zhang, Tianyu Zhang, Wen-qi Zhang
Vehicle re-identification (Re-ID) is very important in intelligent transportation and video surveillance. Prior works focus on extracting discriminative features from visual appearance of vehicles or using visual-spatio-temporal information. However, background interference in vehicle re-identification have not been explored. In the actual large-scale spatio-temporal scenes, the same vehicle usually appears in different backgrounds while different vehicles might appear in the same background, which will seriously affect the re-identification performance.
1 code implementation • 24 Sep 2019 • Tianyu Zhang, Lingxi Xie, Longhui Wei, Yongfei Zhang, Bo Li, Qi Tian
Differently, this paper investigates ReID in an unexplored single-camera-training (SCT) setting, where each person in the training set appears in only one camera.
no code implementations • 16 Nov 2018 • Tianyu Zhang, Liwei Zhang, Philip R. O. Payne, Fuhai Li
Drug resistance is still a major challenge in cancer therapy.