no code implementations • ECCV 2020 • Qing Liu, Orchid Majumder, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
This process enables incrementally improving the model by processing multiple learning episodes, each representing a different learning task, even with few training examples.
1 code implementation • 29 May 2025 • Jianwei Wang, Mengqi Wang, Yinsi Zhou, Zhenchang Xing, Qing Liu, Xiwei Xu, Wenjie Zhang, Liming Zhu
Health, Safety, and Environment (HSE) compliance assessment demands dynamic real-time decision-making under complicated regulations and complex human-machine-environment interactions.
no code implementations • 23 May 2025 • Xingyu Li, Qing Liu, Tony Jiang, Hong Amy Xia, Brian P. Hobbs, Peng Wei
We propose a novel method, termed the M-learner, for estimating heterogeneous indirect and total treatment effects and identifying relevant subgroups within a mediation framework.
no code implementations • 20 May 2025 • Zongyuan Deng, Yujie Cai, Qing Liu, Shiyao Mu, Bin Lyu, Zhen Yang
The selection of base station sites is a critical challenge in 5G network planning, which requires efficient optimization of coverage, cost, user satisfaction, and practical constraints.
1 code implementation • CVPR 2025 • Ali Salar, Qing Liu, YingLi Tian, Guoying Zhao
The rapid growth of social media has led to the widespread sharing of individual portrait images, which pose serious privacy risks due to the capabilities of automatic face recognition (AFR) systems for mass surveillance.
no code implementations • CVPR 2025 • Xin Yu, Tianyu Wang, Soo Ye Kim, Paul Guerrero, Xi Chen, Qing Liu, Zhe Lin, Xiaojuan Qi
Simple as it seems, moving an object to another location within an image is, in fact, a challenging image-editing task that requires re-harmonizing the lighting, adjusting the pose based on perspective, accurately filling occluded regions, and ensuring coherent synchronization of shadows and reflections while maintaining the object identity.
no code implementations • 6 Mar 2025 • Yiting Wei, Bingo Wing-Kuen Ling, Danni Chen, Yuheng Dai, Qing Liu
If the accumulate probability of any selected optimization method at a point is greater than a threshold value, then the accumulate probabilities of these three selected optimization methods at that point are reset to zero.
1 code implementation • 20 Feb 2025 • Yuming Yang, Jiang Zhong, Li Jin, Jingwang Huang, Jingpeng Gao, Qing Liu, Yang Bai, Jingyuan Zhang, Rui Jiang, Kaiwen Wei
Multimodal Retrieval-Augmented Generation (MRAG) enhances reasoning capabilities by integrating external knowledge.
no code implementations • 29 Jan 2025 • Yihao Liu, Zhihao Cui, Liming Li, Junjie You, Xinle Feng, Jianxin Wang, Xiangyu Wang, Qing Liu, Minghua Wu
Gliomas are the most common primary tumors of the central nervous system.
no code implementations • CVPR 2025 • Shaoteng Liu, Tianyu Wang, Jui-Hsien Wang, Qing Liu, Zhifei Zhang, Joon-Young Lee, Yijun Li, Bei Yu, Zhe Lin, Soo Ye Kim, Jiaya Jia
Large-scale video generation models have the inherent ability to realistically model natural scenes.
no code implementations • CVPR 2025 • Xi Chen, Zhifei Zhang, He Zhang, Yuqian Zhou, Soo Ye Kim, Qing Liu, Yijun Li, Jianming Zhang, Nanxuan Zhao, Yilin Wang, Hui Ding, Zhe Lin, Hengshuang Zhao
We introduce UniReal, a unified framework designed to address various image generation and editing tasks.
no code implementations • 5 Dec 2024 • Yusuf Dalva, Yijun Li, Qing Liu, Nanxuan Zhao, Jianming Zhang, Zhe Lin, Pinar Yanardag
In this paper, we propose a novel image generation pipeline based on Latent Diffusion Models (LDMs) that generates images with two layers: a foreground layer (RGBA) with transparency information and a background layer (RGB).
no code implementations • CVPR 2025 • Jinrui Yang, Qing Liu, Yijun Li, Soo Ye Kim, Daniil Pakhomov, Mengwei Ren, Jianming Zhang, Zhe Lin, Cihang Xie, Yuyin Zhou
Layered representations, which allow for independent editing of image components, are essential for user-driven content creation, yet existing approaches often struggle to decompose image into plausible layers with accurately retained transparent visual effects such as shadows and reflections.
no code implementations • CVPR 2025 • Hang Hua, Qing Liu, Lingzhi Zhang, Jing Shi, Zhifei Zhang, Yilin Wang, Jianming Zhang, Jiebo Luo
To support this endeavor, we introduce COMPOSITIONCAP, a new dataset for multi-grained region compositional image captioning, which introduces the task of compositional attribute-aware regional image captioning.
no code implementations • 21 Nov 2024 • Yuanhao Cai, He Zhang, Kai Zhang, Yixun Liang, Mengwei Ren, Fujun Luan, Qing Liu, Soo Ye Kim, Jianming Zhang, Zhifei Zhang, Yuqian Zhou, Yulun Zhang, Xiaokang Yang, Zhe Lin, Alan Yuille
Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency.
1 code implementation • 6 Nov 2024 • Ziyuan Ding, Yixiong Liang, Shichao Kan, Qing Liu
Our method effectively improves the overall segmentation accuracy of fundus lesions while consuming reasonable memory and computational overhead, and maintaining satisfying inference speed.
no code implementations • 22 Oct 2024 • Zhenyuan Yang, Zhengliang Liu, Jing Zhang, Cen Lu, Jiaxin Tai, Tianyang Zhong, Yiwei Li, Siyan Zhao, Teng Yao, Qing Liu, Jinlin Yang, Qixin Liu, Zhaowei Li, Kexin Wang, Longjun Ma, Dajiang Zhu, Yudan Ren, Bao Ge, Wei zhang, Ning Qiang, Tuo Zhang, Tianming Liu
This study examines the capabilities of advanced Large Language Models (LLMs), particularly the o1 model, in the context of literary analysis.
1 code implementation • 18 Oct 2024 • Xingyu Tan, Xiaoyang Wang, Qing Liu, Xiwei Xu, Xin Yuan, Wenjie Zhang
In order to improve the efficiency, PoG prunes irrelevant information from the graph exploration first and introduces efficient three-step pruning techniques that incorporate graph structures, LLM prompting, and a pre-trained language model (e. g., SBERT) to effectively narrow down the explored candidate paths.
Ranked #1 on
Knowledge Base Question Answering
on ComplexWebQuestions
(EM metric)
1 code implementation • 22 Sep 2024 • Yuming Jiang, Nanxuan Zhao, Qing Liu, Krishna Kumar Singh, Shuai Yang, Chen Change Loy, Ziwei Liu
The training data engine covers the diverse needs of group portrait editing.
no code implementations • 30 Jul 2024 • Yue Pan, Qile Liu, Qing Liu, Li Zhang, Gan Huang, Xin Chen, Fali Li, Peng Xu, Zhen Liang
To address this issue, we propose a Dual Attentive (DuA) transformer framework for long-term continuous EEG emotion analysis.
no code implementations • 12 Jun 2024 • Xianhang Li, Haoqin Tu, Mude Hui, Zeyu Wang, Bingchen Zhao, Junfei Xiao, Sucheng Ren, Jieru Mei, Qing Liu, Huangjie Zheng, Yuyin Zhou, Cihang Xie
For discriminative models like CLIP, we observe enhanced zero-shot performance in cross-modal retrieval tasks.
Ranked #127 on
Visual Question Answering
on MM-Vet
no code implementations • 11 Jun 2024 • Zhengzhe Liu, Qing Liu, Chirui Chang, Jianming Zhang, Daniil Pakhomov, Haitian Zheng, Zhe Lin, Daniel Cohen-Or, Chi-Wing Fu
Deoccluding the hidden portions of objects in a scene is a formidable task, particularly when addressing real-world scenes.
no code implementations • 4 Jun 2024 • Danqing Hu, Shanyuan Zhang, Qing Liu, Xiaofeng Zhu, Bing Liu
Besides the automatic quantitative evaluation metrics, we define five human evaluation metrics, i. e., completeness, correctness, conciseness, verisimilitude, and replaceability, to evaluate the semantics of the generated impressions.
no code implementations • 8 Apr 2024 • Jing Gu, Nanxuan Zhao, Wei Xiong, Qing Liu, Zhifei Zhang, He Zhang, Jianming Zhang, HyunJoon Jung, Yilin Wang, Xin Eric Wang
Compared with existing methods for personalized subject swapping, SwapAnything has three unique advantages: (1) precise control of arbitrary objects and parts rather than the main subject, (2) more faithful preservation of context pixels, (3) better adaptation of the personalized concept to the image.
no code implementations • 11 Jan 2024 • Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky
We describe MGARD, a software providing MultiGrid Adaptive Reduction for floating-point scientific data on structured and unstructured grids.
1 code implementation • CVPR 2024 • Nannan Li, Qing Liu, Krishna Kumar Singh, Yilin Wang, Jianming Zhang, Bryan A. Plummer, Zhe Lin
In this paper, we propose UniHuman, a unified model that addresses multiple facets of human image editing in real-world settings.
no code implementations • CVPR 2024 • Jaskirat Singh, Jianming Zhang, Qing Liu, Cameron Smith, Zhe Lin, Liang Zheng
To overcome these limitations, we introduce SmartMask, which allows any novice user to create detailed masks for precise object insertion.
no code implementations • 6 Nov 2023 • Hanrong Ye, Jason Kuen, Qing Liu, Zhe Lin, Brian Price, Dan Xu
On the highly competitive ADE20K and COCO benchmarks, our data generation method markedly improves the performance of state-of-the-art segmentation models in semantic segmentation, panoptic segmentation, and instance segmentation.
1 code implementation • ICCV 2023 • Lingzhi Zhang, Zhengjie Xu, Connelly Barnes, Yuqian Zhou, Qing Liu, He Zhang, Sohrab Amirghodsi, Zhe Lin, Eli Shechtman, Jianbo Shi
Recent advancements in deep generative models have facilitated the creation of photo-realistic images across various tasks.
no code implementations • 11 Aug 2023 • Fanglong Yao, Changyuan Tian, Jintao Liu, Zequn Zhang, Qing Liu, Li Jin, Shuchao Li, Xiaoyu Li, Xian Sun
Inspired by this, this paper innovatively proposes a multimodal Hypergraph-of-Thought (HoT) reasoning paradigm, which enables the foundation models to possess the expert-level ability of high-order multi-hop reasoning and multimodal comparative judgement.
1 code implementation • CVPR 2023 • Tai-Yu Pan, Qing Liu, Wei-Lun Chao, Brian Price
Second, we introduce a novel approach to improve part segmentation on unseen objects, inspired by an interesting finding -- for unseen objects, the pixel-wise features extracted by the model often reveal high-quality part segments.
no code implementations • 12 Apr 2023 • Shiwei Zhang, Zhengzheng Wang, Qing Liu, Fei Wang, Wei Ke, Tong Zhang
This paper presents a new annotation method called Sparse Annotation (SA) for crowd counting, which reduces human labeling efforts by sparsely labeling individuals in an image.
no code implementations • 3 Apr 2023 • Minjun Zhao, Yichen Yin, YUREN MAO, Qing Liu, Lu Chen, Yunjun Gao
Recently, a few methods have been put forward to handle the SGA dilemma.
no code implementations • 27 Feb 2023 • Linhao Zhang, Li Jin, Xian Sun, Guangluan Xu, Zequn Zhang, Xiaoyu Li, Nayu Liu, Qing Liu, Shiyao Yan
Multimodal hate detection, which aims to identify harmful content online such as memes, is crucial for building a wholesome internet environment.
no code implementations • 21 Feb 2023 • Yunzhong He, Cong Zhang, Ruoyan Kong, Chaitanya Kulkarni, Qing Liu, Ashish Gandhe, Amit Nithianandan, Arul Prakash
Query categorization at customer-to-customer e-commerce platforms like Facebook Marketplace is challenging due to the vagueness of search intent, noise in real-world data, and imbalanced training data across languages.
1 code implementation • 22 Dec 2022 • Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, Todor Mihaylov, Daniel Simig, Ping Yu, Kurt Shuster, Tianlu Wang, Qing Liu, Punit Singh Koura, Xian Li, Brian O'Horo, Gabriel Pereyra, Jeff Wang, Christopher Dewan, Asli Celikyilmaz, Luke Zettlemoyer, Ves Stoyanov
To this end, we create OPT-IML Bench: a large benchmark for Instruction Meta-Learning (IML) of 2000 NLP tasks consolidated into task categories from 8 existing benchmarks, and prepare an evaluation framework to measure three types of model generalizations: to tasks from fully held-out categories, to held-out tasks from seen categories, and to held-out instances from seen tasks.
Ranked #26 on
Natural Language Inference
on RTE
no code implementations • 13 Dec 2022 • Haitian Zheng, Zhe Lin, Jingwan Lu, Scott Cohen, Eli Shechtman, Connelly Barnes, Jianming Zhang, Qing Liu, Yuqian Zhou, Sohrab Amirghodsi, Jiebo Luo
Moreover, the object-level discriminators take aligned instances as inputs to enforce the realism of individual objects.
no code implementations • CVPR 2023 • Yu Zeng, Zhe Lin, Jianming Zhang, Qing Liu, John Collomosse, Jason Kuen, Vishal M. Patel
We propose a new framework for conditional image synthesis from semantic layouts of any precision levels, ranging from pure text to a 2D semantic canvas with precise shapes.
no code implementations • 19 Nov 2022 • Yi Yang, Zhong-Qiu Zhao, Quan Bai, Qing Liu, Weihua Li
Due to the dynamic nature, the proposed algorithms can also estimate true labels online without re-visiting historical data.
no code implementations • 7 Nov 2022 • Qing Liu, Wenli Yang, Shiqing Wu
Over the past two decades, PKAW has provided a forum for researchers and practitioners to discuss the state-of-the-arts in the area of knowledge acquisition and machine intelligence (MI, also Artificial Intelligence, AI).
1 code implementation • 11 Jul 2022 • Yixiong Liang, Shuo Feng, Qing Liu, Hulin Kuang, Jianfeng Liu, Liyan Liao, Yun Du, Jianxin Wang
To mimic these behaviors, we propose to explore contextual relationships to boost the performance of cervical abnormal cell detection.
no code implementations • 7 Jun 2022 • Jinkai Tian, Xiaoyu Sun, Yuxuan Du, Shanshan Zhao, Qing Liu, Kaining Zhang, Wei Yi, Wanrong Huang, Chaoyue Wang, Xingyao Wu, Min-Hsiu Hsieh, Tongliang Liu, Wenjing Yang, DaCheng Tao
Due to the intrinsic probabilistic nature of quantum mechanics, it is reasonable to postulate that quantum generative learning models (QGLMs) may surpass their classical counterparts.
1 code implementation • ACL 2022 • Jiawei Chen, Qing Liu, Hongyu Lin, Xianpei Han, Le Sun
In this paper, we propose a self-describing mechanism for few-shot NER, which can effectively leverage illustrative instances and precisely transfer knowledge from external resources by describing both entity types and mentions using a universal concept set.
2 code implementations • ACL 2022 • Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu
Information extraction suffers from its varying targets, heterogeneous structures, and demand-specific schemas.
Ranked #5 on
Aspect-Based Sentiment Analysis (ABSA)
on ASTE
(using extra training data)
no code implementations • 22 Jan 2022 • Jingwen Zhang, Qing Liu, Haorui Zhang, Michelle Dai, Qianqian Song, Defu Yang, Guorong Wu, Minghan Chen
Background: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-\b{eta} (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive.
no code implementations • 5 Dec 2021 • Qing Wang, Qing Liu, Zihao Zhang, HaoYu Fang, Xi Zheng
Artificial intelligence (AI) based device identification improves the security of the internet of things (IoT), and accelerates the authentication process.
1 code implementation • 30 Oct 2021 • Qing Liu, Haotian Liu, Wei Ke, Yixiong Liang
It reassembles features in a dimension-reduced feature space and simultaneously aggregates multiple features inside a large predefined region into multiple target features.
no code implementations • 26 Oct 2021 • Yixiao Zhang, Adam Kortylewski, Qing Liu, Seyoun Park, Benjamin Green, Elizabeth Engle, Guillermo Almodovar, Ryan Walk, Sigfredo Soto-Diaz, Janis Taube, Alex Szalay, Alan Yuille
It only requires annotations on isolated nucleus, rather than on all nuclei in the dataset.
no code implementations • 18 Oct 2021 • Yunjia Xi, Weiwen Liu, Xinyi Dai, Ruiming Tang, Weinan Zhang, Qing Liu, Xiuqiang He, Yong Yu
As a critical task for large-scale commercial recommender systems, reranking has shown the potential of improving recommendation results by uncovering mutual influence among items.
no code implementations • EMNLP 2021 • Qing Liu, Hongyu Lin, Xinyan Xiao, Xianpei Han, Le Sun, Hua Wu
Conventional entity typing approaches are based on independent classification paradigms, which make them difficult to recognize inter-dependent, long-tailed and fine-grained entity types.
Ranked #8 on
Entity Typing
on Open Entity
no code implementations • 23 Aug 2021 • Qing Liu, Longbing Cao
Different from existing COVID-19 models, SUDR characterizes the undocumented infections during unknown transmission processes.
no code implementations • 9 Jun 2021 • Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He
The field-wise transfer policy decides how the pre-trained embedding representations are frozen or fine-tuned based on the given instance from the target domain.
no code implementations • 14 May 2021 • Nicholas Ichien, Qing Liu, Shuhao Fu, Keith J. Holyoak, Alan Yuille, Hongjing Lu
We compared human performance to that of two recent deep learning models (Siamese Network and Relation Network) directly trained to solve these analogy problems, as well as to that of a compositional model that assesses relational similarity between part-based representations.
no code implementations • NAACL 2021 • Anish Acharya, Suranjit Adhikari, Sanchit Agarwal, Vincent Auvray, Nehal Belgamwar, Arijit Biswas, Shubhra Chandra, Tagyoung Chung, Maryam Fazel-Zarandi, Raefer Gabriel, Shuyang Gao, Rahul Goel, Dilek Hakkani-Tur, Jan Jezabek, Abhay Jha, Jiun-Yu Kao, Prakash Krishnan, Peter Ku, Anuj Goyal, Chien-Wei Lin, Qing Liu, Arindam Mandal, Angeliki Metallinou, Vishal Naik, Yi Pan, Shachi Paul, Vittorio Perera, Abhishek Sethi, Minmin Shen, Nikko Strom, Eddie Wang
Finally, we evaluate our system using a typical movie ticket booking task and show that the dialogue simulator is an essential component of the system that leads to over $50\%$ improvement in turn-level action signature prediction accuracy.
no code implementations • 16 Apr 2021 • Longbing Cao, Qing Liu
The SARS-CoV-2 virus and COVID-19 disease have posed unprecedented and overwhelming demand, challenges and opportunities to domain, model and data driven modeling.
1 code implementation • CVPR 2022 • Qing Liu, Adam Kortylewski, Zhishuai Zhang, Zizhang Li, Mengqi Guo, Qihao Liu, Xiaoding Yuan, Jiteng Mu, Weichao Qiu, Alan Yuille
We believe our dataset provides a rich testbed to study UDA for part segmentation and will help to significantly push forward research in this area.
no code implementations • CVPR 2021 • Qing Liu, Vignesh Ramanathan, Dhruv Mahajan, Alan Yuille, Zhenheng Yang
However, existing approaches which rely only on image-level class labels predominantly suffer from errors due to (a) partial segmentation of objects and (b) missing object predictions.
no code implementations • 7 Mar 2021 • Qing Liu, Defu Yang, Jingwen Zhang, Ziming Wei, Guorong Wu, Minghan Chen
Three major biomarkers: beta-amyloid (A), pathologic tau (T), and neurodegeneration (N), are recognized as valid proxies for neuropathologic changes of Alzheimer's disease.
no code implementations • 26 Feb 2021 • Cheng Xie, Ting Zeng, Hongxin Xiang, Keqin Li, Yun Yang, Qing Liu
The approach also applies a semi-supervised learning process to re-train knowledge-to-visual model.
no code implementations • 25 Jan 2021 • Cheng Xie, Hongxin Xiang, Ting Zeng, Yun Yang, Beibei Yu, Qing Liu
CKL enables more relevant semantic features to be trained for semantic-to-visual feature embedding in ZSL, while Taxonomy Regularization (TR) significantly improves the intersections with unseen images with more generalized visual features generated from generative network.
no code implementations • 31 Dec 2020 • Ziwen Xu, Beiji Zou, Qing Liu
Dual-branch SalStructIQA contains two CNN branches and one is guided by large-size salient structures while the other is guided by tiny-size salient structures.
no code implementations • 3 Dec 2020 • Qing Liu, Haotian Liu, Yixiong Liang
In detail, for the first branch, we use a uniform sampler to sample pixels from predicted segmentation mask for Dice loss calculation, which leads to this branch naturally be biased in favour of large hard exudates as Dice loss generates larger cost on misidentification of large hard exudates than small hard exudates.
no code implementations • 1 Nov 2020 • Xinyi Dai, Jiawei Hou, Qing Liu, Yunjia Xi, Ruiming Tang, Weinan Zhang, Xiuqiang He, Jun Wang, Yong Yu
To this end, we propose a novel ranking framework called U-rank that directly optimizes the expected utility of the ranking list.
no code implementations • 26 Oct 2020 • Ziwen Xu, Beiji Zou, Qing Liu
Retinal image quality assessment is an essential task in the diagnosis of retinal diseases.
no code implementations • 28 Jun 2020 • Adam Kortylewski, Qing Liu, Angtian Wang, Yihong Sun, Alan Yuille
The structure of the compositional model enables CompositionalNets to decompose images into objects and context, as well as to further decompose object representations in terms of individual parts and the objects' pose.
1 code implementation • SoftwareX 2020 • William F. Godoy, Norbert Podhorszki, Ruonan Wang, Chuck Atkins, Greg Eisenhauer, Junmin Gu, Philip Davis, Jong Choi, Kai Germaschewski, Kevin Huck, Axel Huebl, Mark Kim, James Kress, Tahsin Kurc, Qing Liu, Jeremy Logan, Kshitij Mehta, George Ostrouchov, Manish Parashar, Franz Poeschel, David Pugmire, Eric Suchyta, Keichi Takahashi, Nick Thompson, Seiji Tsutsumi, Lipeng Wan, Matthew Wolf, Kesheng Wu, Scott Klasky
We present ADIOS 2, the latest version of the Adaptable Input Output (I/O) System.
1 code implementation • CVPR 2020 • Adam Kortylewski, Ju He, Qing Liu, Alan Yuille
Inspired by the success of compositional models at classifying partially occluded objects, we propose to integrate compositional models and DCNNs into a unified deep model with innate robustness to partial occlusion.
no code implementations • 11 Feb 2020 • Qing Liu, Orchid Majumder, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Majority of the modern meta-learning methods for few-shot classification tasks operate in two phases: a meta-training phase where the meta-learner learns a generic representation by solving multiple few-shot tasks sampled from a large dataset and a testing phase, where the meta-learner leverages its learnt internal representation for a specific few-shot task involving classes which were not seen during the meta-training phase.
no code implementations • 18 Nov 2019 • Adam Kortylewski, Qing Liu, Huiyu Wang, Zhishuai Zhang, Alan Yuille
Our experimental results demonstrate that the proposed extensions increase the model's performance at localizing occluders as well as at classifying partially occluded objects.
no code implementations • 5 Nov 2019 • Qing Liu, Beiji Zou, Yang Zhao, Yixiong Liang
To build connections among prediction branches, this paper introduces gradient boosting framework to deep classification model and proposes a gradient boosting network called BoostNet.
no code implementations • 11 Sep 2019 • Yukun Zhou, Zailiang Chen, Hailan Shen, Qing Liu, Rongchang Zhao, Yixiong Liang
In each branch, the input feature map is deduced into an enhancement map and a mask map, thereby highlighting the most discriminative parts or hiding them.
no code implementations • 28 May 2019 • Adam Kortylewski, Qing Liu, Huiyu Wang, Zhishuai Zhang, Alan Yuille
In this work, we combine DCNNs and compositional object models to retain the best of both approaches: a discriminative model that is robust to partial occlusion and mask attacks.
no code implementations • 18 Apr 2019 • Qing Liu, Xiaopeng Hong, Wei Ke, Zailiang Chen, Beiji Zou
In this paper, we propose a novel segmentation approach, named Cartesian-polar dual-domain network (DDNet), which for the first time considers the complementary of the Cartesian domain and the polar domain.
1 code implementation • ICCV 2019 • Qing Liu, Lingxi Xie, Huiyu Wang, Alan Yuille
Sketch-based image retrieval (SBIR) is widely recognized as an important vision problem which implies a wide range of real-world applications.
no code implementations • 27 Dec 2018 • Chandra Khatri, Behnam Hedayatnia, Anu Venkatesh, Jeff Nunn, Yi Pan, Qing Liu, Han Song, Anna Gottardi, Sanjeev Kwatra, Sanju Pancholi, Ming Cheng, Qinglang Chen, Lauren Stubel, Karthik Gopalakrishnan, Kate Bland, Raefer Gabriel, Arindam Mandal, Dilek Hakkani-Tur, Gene Hwang, Nate Michel, Eric King, Rohit Prasad
In the second iteration of the competition in 2018, university teams advanced the state of the art by using context in dialog models, leveraging knowledge graphs for language understanding, handling complex utterances, building statistical and hierarchical dialog managers, and leveraging model-driven signals from user responses.
1 code implementation • ICCV 2019 • Yutong Bai, Qing Liu, Lingxi Xie, Weichao Qiu, Yan Zheng, Alan Yuille
In particular, this enables images in the training dataset to be matched to a virtual 3D model of the object (for simplicity, we assume that the object viewpoint can be estimated by standard techniques).
1 code implementation • 14 Oct 2018 • Yixiong Liang, Zhihong Tang, Meng Yan, Jialin Chen, Qing Liu, Yao Xiang
In this paper we propose an efficient CNN-based object detection methods for cervical cancer cells/clumps detection.
no code implementations • 11 Jan 2018 • Ashwin Ram, Rohit Prasad, Chandra Khatri, Anu Venkatesh, Raefer Gabriel, Qing Liu, Jeff Nunn, Behnam Hedayatnia, Ming Cheng, Ashish Nagar, Eric King, Kate Bland, Amanda Wartick, Yi Pan, Han Song, Sk Jayadevan, Gene Hwang, Art Pettigrue
This paper outlines the advances created by the university teams as well as the Alexa Prize team to achieve the common goal of solving the problem of Conversational
no code implementations • ICLR 2018 • Boyang Deng, Qing Liu, Siyuan Qiao, Alan Yuille
Our models are based on the idea of encoding objects in terms of visual concepts, which are interpretable visual cues represented by the feature vectors within CNNs.
no code implementations • 22 Nov 2017 • Boyang Deng, Qing Liu, Siyuan Qiao, Alan Yuille
In this work, we address these limitations of CNNs by developing novel, flexible, and interpretable models for few-shot learning.