1 code implementation • NAACL 2022 • Shu Liu, Kaiwen Li, Zuhe Li
Aspect sentiment triplet extraction (ASTE) is a challenging subtask in aspect-based sentiment analysis.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2
no code implementations • ECCV 2020 • Zetong Yang, Yanan sun, Shu Liu, Xiaojuan Qi, Jiaya Jia
In 3D recognition, to fuse multi-scale structure information, existing methods apply hierarchical frameworks stacked by multiple fusion layers for integrating current relative locations with structure information from the previous level.
1 code implementation • 24 Apr 2024 • Shu Liu, Yan Xu, Tongming Wan, Xiaoyan Kui
One auxiliary branch is constructed to obtain the label distributions of samples.
Facial Expression Recognition Facial Expression Recognition (FER)
2 code implementations • 11 Apr 2024 • Bohao Peng, Zhuotao Tian, Shu Liu, MingChang Yang, Jiaya Jia
In this study, we introduce the Scalable Language Model (SLM) to overcome these limitations within a more challenging and generalized setting, representing a significant advancement toward practical applications for continual learning.
no code implementations • 9 Mar 2024 • Shu Liu, Asim Biswal, Audrey Cheng, Xiangxi Mo, Shiyi Cao, Joseph E. Gonzalez, Ion Stoica, Matei Zaharia
In this paper, we explore how to optimize LLM inference for analytical workloads that invoke LLMs within relational queries.
no code implementations • 29 Feb 2024 • Shaoteng Liu, Haoqi Yuan, Minda Hu, Yanwei Li, Yukang Chen, Shu Liu, Zongqing Lu, Jiaya Jia
To seamlessly integrate both modalities, we introduce a two-level hierarchical framework, RL-GPT, comprising a slow agent and a fast agent.
no code implementations • 5 Jan 2024 • Jingyao Li, Pengguang Chen, Shaozuo Yu, Shu Liu, Jiaya Jia
The crux of effective out-of-distribution (OOD) detection lies in acquiring a robust in-distribution (ID) representation, distinct from OOD samples.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
1 code implementation • 1 Jan 2024 • Shu Liu, Shangqing Zhao, Chenghao Jia, Xinlin Zhuang, Zhaoguang Long, Qingquan Wu, Chong Yang, Aimin Zhou, Man Lan
To bridge this gap, we introduce BIBench, a comprehensive benchmark designed to evaluate the data analysis capabilities of LLMs within the context of Business Intelligence (BI).
2 code implementations • 28 Dec 2023 • Zhongshen Zeng, Pengguang Chen, Shu Liu, Haiyun Jiang, Jiaya Jia
In this work, we introduce a novel evaluation paradigm for Large Language Models, one that challenges them to engage in meta-reasoning.
no code implementations • 28 Dec 2023 • Senqiao Yang, Tianyuan Qu, Xin Lai, Zhuotao Tian, Bohao Peng, Shu Liu, Jiaya Jia
While LISA effectively bridges the gap between segmentation and large language models to enable reasoning segmentation, it poses certain limitations: unable to distinguish different instances of the target region, and constrained by the pre-defined textual response formats.
1 code implementation • 26 Dec 2023 • Jingyao Li, Pengguang Chen, Shaozuo Yu, Shu Liu, Jiaya Jia
Experimental results demonstrate that, when labeling 80% of the samples, the performance of the current SOTA method declines by 0. 74%, whereas our proposed BAL achieves performance comparable to the full dataset.
1 code implementation • 7 Dec 2023 • Yuechen Zhang, Shengju Qian, Bohao Peng, Shu Liu, Jiaya Jia
Without tuning on LLaVA-v1. 5, our method secured 70. 7 in the MMBench test and 1552. 5 in MME-perception.
1 code implementation • 7 Nov 2023 • Shu Liu, Cameron Lai, Fujio Toriumi
The results underscore the superior performance of HyperS2V in terms of both interpretability and applicability to downstream tasks.
no code implementations • 26 Oct 2023 • Shuai Yang, Zhifei Chen, Pengguang Chen, Xi Fang, Shu Liu, Yingcong Chen
Defect inspection is paramount within the closed-loop manufacturing system.
no code implementations • 20 Oct 2023 • Feng Zhang, Rui Bao, Congqi Dai, Wanlu Zhang, Shu Liu, Ruiqian Guo
The results show that for both models there are always some non-pure white light sources, whose accuracy is better than pure white light, which suggests the potential of multi-spectral light sources to further enhance the effectiveness of machine vision.
1 code implementation • 5 Oct 2023 • Shuai Yang, Yukang Chen, Luozhou Wang, Shu Liu, Yingcong Chen
Denoising Diffusion Probabilistic Models (DDPMs) have garnered popularity for data generation across various domains.
1 code implementation • 23 Aug 2023 • Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu, James T. Kwok
Multi-task learning (MTL), a learning paradigm to learn multiple related tasks simultaneously, has achieved great success in various fields.
2 code implementations • 1 Aug 2023 • Xin Lai, Zhuotao Tian, Yukang Chen, Yanwei Li, Yuhui Yuan, Shu Liu, Jiaya Jia
In this work, we propose a new segmentation task -- reasoning segmentation.
1 code implementation • ICCV 2023 • Luozhou Wang, Shuai Yang, Shu Liu, Ying-Cong Chen
Conditional diffusion models have demonstrated impressive performance in image manipulation tasks.
no code implementations • 27 Jun 2023 • Bohao Peng, Zhuotao Tian, Xiaoyang Wu, Chengyao Wang, Shu Liu, Jingyong Su, Jiaya Jia
We hope our work can benefit broader industrial applications where novel classes with limited annotations are required to be decently identified.
1 code implementation • ICASSP 2023 • Shu Liu, Yan Xu, Tongming Wan, Xiaoyan Kui
One auxiliary branch is constructed to obtain the label distributions of samples.
Ranked #1 on Facial Expression Recognition (FER) on SFEW
no code implementations • CVPR 2023 • Tao Hu, Xiaogang Xu, Shu Liu, Jiaya Jia
Also, we present Point Encoding to build Multi-scale Radiance Fields that provide discriminative 3D point features.
1 code implementation • CVPR 2023 • Bohao Peng, Zhuotao Tian, Xiaoyang Wu, Chenyao Wang, Shu Liu, Jingyong Su, Jiaya Jia
Few-shot semantic segmentation (FSS) aims to form class-agnostic models segmenting unseen classes with only a handful of annotations.
Ranked #6 on Few-Shot Semantic Segmentation on COCO-20i (1-shot)
2 code implementations • 21 Mar 2023 • Zhuotao Tian, Jiequan Cui, Li Jiang, Xiaojuan Qi, Xin Lai, Yixin Chen, Shu Liu, Jiaya Jia
Semantic segmentation is still a challenging task for parsing diverse contexts in different scenes, thus the fixed classifier might not be able to well address varying feature distributions during testing.
1 code implementation • ICCV 2023 • Wenhang Ge, Tao Hu, Haoyu Zhao, Shu Liu, Ying-Cong Chen
We show that together with a reflection direction-dependent radiance, our model achieves high-quality surface reconstruction on reflective surfaces and outperforms the state-of-the-arts by a large margin.
1 code implementation • CVPR 2023 • Jingyao Li, Pengguang Chen, Shaozuo Yu, Zexin He, Shu Liu, Jiaya Jia
The core of out-of-distribution (OOD) detection is to learn the in-distribution (ID) representation, which is distinguishable from OOD samples.
Ranked #12 on Out-of-Distribution Detection on ImageNet-1k vs Places (AUROC metric)
1 code implementation • 4 Dec 2022 • Shu Liu, Enquan Huang, Ziyu Zhou, Yan Xu, Xiaoyan Kui, Tao Lei, Hongying Meng
The data processing is simplified to a minimum for a lightweight design, and MobileNetV2 is selected as our backbone.
4 code implementations • 26 Sep 2022 • Jiequan Cui, Zhisheng Zhong, Zhuotao Tian, Shu Liu, Bei Yu, Jiaya Jia
Based on theoretical analysis, we observe that supervised contrastive loss tends to bias high-frequency classes and thus increases the difficulty of imbalanced learning.
Ranked #5 on Long-tail Learning on iNaturalist 2018
no code implementations • 20 Jul 2022 • Laxmi Pandey, Debjyoti Paul, Pooja Chitkara, Yutong Pang, Xuedong Zhang, Kjell Schubert, Mark Chou, Shu Liu, Yatharth Saraf
Inverse text normalization (ITN) is used to convert the spoken form output of an automatic speech recognition (ASR) system to a written form.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
1 code implementation • 20 Jul 2022 • Xin Lai, Zhuotao Tian, Xiaogang Xu, Yingcong Chen, Shu Liu, Hengshuang Zhao, LiWei Wang, Jiaya Jia
Unsupervised domain adaptation in semantic segmentation has been raised to alleviate the reliance on expensive pixel-wise annotations.
1 code implementation • 2 Jun 2022 • Tao Hu, Shu Liu, Yilun Chen, Tiancheng Shen, Jiaya Jia
Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes.
1 code implementation • 6 Apr 2022 • Yilun Chen, Shijia Huang, Shu Liu, Bei Yu, Jiaya Jia
First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features.
4 code implementations • CVPR 2022 • Xin Lai, Jianhui Liu, Li Jiang, LiWei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, Jiaya Jia
In this paper, we propose Stratified Transformer that is able to capture long-range contexts and demonstrates strong generalization ability and high performance.
Ranked #15 on Semantic Segmentation on ScanNet
no code implementations • 2 Mar 2022 • Yixin Chen, Zhuotao Tian, Pengguang Chen, Shu Liu, Jiaya Jia
We revisit the one- and two-stage detector distillation tasks and present a simple and efficient semantic-aware framework to fill the gap between them.
no code implementations • CVPR 2022 • Tao Hu, Shu Liu, Yilun Chen, Tiancheng Shen, Jiaya Jia
Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes.
1 code implementation • ICCV 2021 • Li Jiang, Shaoshuai Shi, Zhuotao Tian, Xin Lai, Shu Liu, Chi-Wing Fu, Jiaya Jia
To address the high cost and challenges of 3D point-level labeling, we present a method for semi-supervised point cloud semantic segmentation to adopt unlabeled point clouds in training to boost the model performance.
1 code implementation • ICCV 2021 • Yixin Chen, Pengguang Chen, Shu Liu, LiWei Wang, Jiaya Jia
Effectively structuring deep knowledge plays a pivotal role in transfer from teacher to student, especially in semantic vision tasks.
no code implementations • 30 Aug 2021 • Pengguang Chen, Yixin Chen, Shu Liu, MingChang Yang, Jiaya Jia
We analyze the reason behind this phenomenon, and propose a novel irregular patch embedding module and adaptive patch fusion module to improve the performance.
1 code implementation • ICCV 2021 • Fan Lu, Guang Chen, Yinlong Liu, Lijun Zhang, Sanqing Qu, Shu Liu, Rongqi Gu
Extensive experiments are conducted on two large-scale outdoor LiDAR point cloud datasets to demonstrate the high accuracy and efficiency of the proposed HRegNet.
5 code implementations • ICCV 2021 • Jiequan Cui, Zhisheng Zhong, Shu Liu, Bei Yu, Jiaya Jia
In this paper, we propose Parametric Contrastive Learning (PaCo) to tackle long-tailed recognition.
Ranked #12 on Long-tail Learning on iNaturalist 2018
2 code implementations • CVPR 2021 • Xin Lai, Zhuotao Tian, Li Jiang, Shu Liu, Hengshuang Zhao, LiWei Wang, Jiaya Jia
Semantic segmentation has made tremendous progress in recent years.
no code implementations • CVPR 2021 • Tao Hu, LiWei Wang, Xiaogang Xu, Shu Liu, Jiaya Jia
Recent single-view 3D reconstruction methods reconstruct object's shape and texture from a single image with only 2D image-level annotation.
1 code implementation • 7 Jun 2021 • Jiaojiao Fan, Shu Liu, Shaojun Ma, Haomin Zhou, Yongxin Chen
Monge map refers to the optimal transport map between two probability distributions and provides a principled approach to transform one distribution to another.
7 code implementations • CVPR 2021 • Pengguang Chen, Shu Liu, Hengshuang Zhao, Jiaya Jia
Knowledge distillation transfers knowledge from the teacher network to the student one, with the goal of greatly improving the performance of the student network.
Ranked #12 on Knowledge Distillation on CIFAR-100
5 code implementations • CVPR 2021 • Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia
Motivated by the fact that predicted probability distributions of classes are highly related to the numbers of class instances, we propose label-aware smoothing to deal with different degrees of over-confidence for classes and improve classifier learning.
Ranked #16 on Long-tail Learning on CIFAR-10-LT (ρ=100)
1 code implementation • CVPR 2021 • Pengguang Chen, Shu Liu, Jiaya Jia
It is even comparable to the contrastive learning methods when only half of training batches are used.
1 code implementation • ICCV 2021 • Huaijia Lin, Ruizheng Wu, Shu Liu, Jiangbo Lu, Jiaya Jia
Video instance segmentation (VIS) aims to segment and associate all instances of predefined classes for each frame in videos.
Ranked #2 on Unsupervised Video Object Segmentation on DAVIS 2017 (val) (using extra training data)
no code implementations • 5 Feb 2021 • Shu Liu, Shaojun Ma, Yongxin Chen, Hongyuan Zha, Haomin Zhou
We propose a new formulation and learning strategy for computing the Wasserstein geodesic between two probability distributions in high dimensions.
5 code implementations • 26 Jan 2021 • Jiequan Cui, Shu Liu, Zhuotao Tian, Zhisheng Zhong, Jiaya Jia
From this perspective, the trivial solution utilizes different branches for the head, medium, and tail classes respectively, and then sums their outputs as the final results is not feasible.
Ranked #20 on Long-tail Learning on iNaturalist 2018
3 code implementations • ICCV 2021 • Jiequan Cui, Shu Liu, LiWei Wang, Jiaya Jia
Previous adversarial training raises model robustness under the compromise of accuracy on natural data.
Ranked #1 on Adversarial Defense on CIFAR-100
1 code implementation • CVPR 2022 • Zhuotao Tian, Xin Lai, Li Jiang, Shu Liu, Michelle Shu, Hengshuang Zhao, Jiaya Jia
Then, since context is essential for semantic segmentation, we propose the Context-Aware Prototype Learning (CAPL) that significantly improves performance by 1) leveraging the co-occurrence prior knowledge from support samples, and 2) dynamically enriching contextual information to the classifier, conditioned on the content of each query image.
no code implementations • ECCV 2020 • Ran Chen, Yong liu, Mengdan Zhang, Shu Liu, Bei Yu, Yu-Wing Tai
Anchor free methods have defined the new frontier in state-of-the-art object detection researches where accurate bounding box estimation is the key to the success of these methods.
2 code implementations • 14 Apr 2020 • Shu Liu, Wei Li, Yunfang Wu, Qi Su, Xu sun
Target-Based Sentiment Analysis aims to detect the opinion aspects (aspect extraction) and the sentiment polarities (sentiment detection) towards them.
2 code implementations • CVPR 2020 • Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, Jiaya Jia
Instance segmentation is an important task for scene understanding.
Ranked #5 on 3D Instance Segmentation on STPLS3D
2 code implementations • CVPR 2020 • Zetong Yang, Yanan sun, Shu Liu, Jiaya Jia
Our method outperforms all state-of-the-art voxel-based single stage methods by a large margin, and has comparable performance to two stage point-based methods as well, with inference speed more than 25 FPS, 2x faster than former state-of-the-art point-based methods.
no code implementations • 10 Feb 2020 • Shaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou
Learning nonlinear dynamics from aggregate data is a challenging problem because the full trajectory of each individual is not available, namely, the individual observed at one time may not be observed at the next time point, or the identity of individual is unavailable.
7 code implementations • 13 Jan 2020 • Pengguang Chen, Shu Liu, Hengshuang Zhao, Xingquan Wang, Jiaya Jia
Then we show limitation of existing information dropping algorithms and propose our structured method, which is simple and yet very effective.
1 code implementation • CVPR 2020 • Yilun Chen, Shu Liu, Xiaoyong Shen, Jiaya Jia
Most state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods.
3 code implementations • 4 Dec 2019 • Hui Ying, Zhaojin Huang, Shu Liu, Tianjia Shao, Kun Zhou
The pixel-level clustering enables EmbedMask to generate high-resolution masks without missing details from repooling, and the existence of proposal embedding simplifies and strengthens the clustering procedure to achieve high speed with higher performance than segmentation-based methods.
Ranked #87 on Instance Segmentation on COCO test-dev
no code implementations • ICCV 2019 • Li Jiang, Hengshuang Zhao, Shu Liu, Xiaoyong Shen, Chi-Wing Fu, Jiaya Jia
To incorporate point features in the edge branch, we establish a hierarchical graph framework, where the graph is initialized from a coarse layer and gradually enriched along the point decoding process.
Ranked #41 on Semantic Segmentation on S3DIS Area5
no code implementations • 9 Sep 2019 • Bernhard Gahr, Shu Liu, Kevin Koch, Filipe Barata, André Dahlinger, Benjamin Ryder, Elgar Fleisch, Felix Wortmann
Building upon existing work, we provide a novel approach for the design of the window length parameter that provides evidence that reliable driver identification can be achieved with data limited to the steering wheel only.
no code implementations • 28 Aug 2019 • Weinong Wang, Wenjie Pei, Qiong Cao, Shu Liu, Yu-Wing Tai
Person re-identification aims to identify whether pairs of images belong to the same person or not.
no code implementations • ICCV 2019 • Yilun Chen, Shu Liu, Xiaoyong Shen, Jiaya Jia
We present a unified, efficient and effective framework for point-cloud based 3D object detection.
no code implementations • ICCV 2019 • Zetong Yang, Yanan sun, Shu Liu, Xiaoyong Shen, Jiaya Jia
We present a new two-stage 3D object detection framework, named sparse-to-dense 3D Object Detector (STD).
3 code implementations • CVPR 2019 • Xinlong Wang, Shu Liu, Xiaoyong Shen, Chunhua Shen, Jiaya Jia
A 3D point cloud describes the real scene precisely and intuitively. To date how to segment diversified elements in such an informative 3D scene is rarely discussed.
Ranked #15 on 3D Instance Segmentation on S3DIS (mRec metric)
no code implementations • 7 Jan 2019 • Hong Zhang, Hao Ouyang, Shu Liu, Xiaojuan Qi, Xiaoyong Shen, Ruigang Yang, Jiaya Jia
With this principle, we present two conceptually simple and yet computational efficient modules, namely Cascade Prediction Fusion (CPF) and Pose Graph Neural Network (PGNN), to exploit underlying contextual information.
Ranked #10 on Pose Estimation on MPII Human Pose
no code implementations • 13 Dec 2018 • Zetong Yang, Yanan sun, Shu Liu, Xiaoyong Shen, Jiaya Jia
We present a novel 3D object detection framework, named IPOD, based on raw point cloud.
Ranked #1 on 3D Object Detection on KITTI Pedestrians Easy
no code implementations • NeurIPS 2018 • Lu Qi, Shu Liu, Jianping Shi, Jiaya Jia
Duplicate removal is a critical step to accomplish a reasonable amount of predictions in prevalent proposal-based object detection frameworks.
no code implementations • 11 Sep 2018 • Shu Liu, Jingjing Xu, Xuancheng Ren, Xu sun
To evaluate the effectiveness of the proposed model, we build a large-scale rationality evaluation dataset.
4 code implementations • ECCV 2018 • Hengshuang Zhao, Yi Zhang, Shu Liu, Jianping Shi, Chen Change Loy, Dahua Lin, Jiaya Jia
We notice information flow in convolutional neural networks is restricted inside local neighborhood regions due to the physical design of convolutional filters, which limits the overall understanding of complex scenes.
Ranked #51 on Semantic Segmentation on Cityscapes test
10 code implementations • CVPR 2018 • Shu Liu, Lu Qi, Haifang Qin, Jianping Shi, Jiaya Jia
The way that information propagates in neural networks is of great importance.
Ranked #3 on Object Detection on iSAID
no code implementations • 6 Dec 2017 • Guang Chen, Shu Liu, Kejia Ren, Zhongnan Qu, Changhong Fu, Gereon Hinz, Alois Knoll
However, the mobile sensing perception brings new challenges for how to efficiently analyze and intelligently interpret the deluge of IoT data in mission- critical services.
no code implementations • ICCV 2017 • Shu Liu, Jiaya Jia, Sanja Fidler, Raquel Urtasun
By exploiting two-directional information, the second network groups horizontal and vertical lines into connected components.
no code implementations • 2 Sep 2016 • Shu Liu, Bo Li, Yangyu Fan, Zhe Guo, Ashok Samal
In order to address the first challenge, this paper recasts facial attractiveness computation as a label distribution learning (LDL) problem rather than a traditional single-label supervised learning task.
no code implementations • CVPR 2016 • Shu Liu, Xiaojuan Qi, Jianping Shi, Hong Zhang, Jiaya Jia
Aiming at simultaneous detection and segmentation (SDS), we propose a proposal-free framework, which detect and segment object instances via mid-level patches.
no code implementations • ICCV 2015 • Xiaojuan Qi, Jianping Shi, Shu Liu, Renjie Liao, Jiaya Jia
In this paper, we propose an object clique potential for semantic segmentation.
no code implementations • ICCV 2015 • Shu Liu, Cewu Lu, Jiaya Jia
Regions-with-convolutional-neural-network (RCNN) is now a commonly employed object detection pipeline.
no code implementations • ICCV 2015 • Cewu Lu, Shu Liu, Jiaya Jia, Chi-Keung Tang
Closed contour is an important objectness indicator.