2 code implementations • 22 May 2025 • Haonian Ji, Shi Qiu, Siyang Xin, Siwei Han, Zhaorun Chen, Hongyi Wang, Dake Zhang, Huaxiu Yao
While foundation models (FMs), such as diffusion models and large vision-language models (LVLMs), have been widely applied in educational contexts, their ability to generate pedagogically effective visual explanations remains limited.
no code implementations • 22 Apr 2025 • Shi Qiu, Shaoyang Guo, Zhuo-Yang Song, Yunbo Sun, Zeyu Cai, Jiashen Wei, Tianyu Luo, Yixuan Yin, Haoxu Zhang, Yi Hu, Chenyang Wang, Chencheng Tang, Haoling Chang, Qi Liu, Ziheng Zhou, Tianyu Zhang, Jingtian Zhang, Zhangyi Liu, Minghao Li, Yuku Zhang, Boxuan Jing, Xianqi Yin, Yutong Ren, Zizhuo Fu, Jiaming Ji, Weike Wang, Xudong Tian, Anqi Lv, Laifu Man, Jianxiang Li, Feiyu Tao, Qihua Sun, Zhou Liang, Yushu Mu, Zhongxuan Li, Jing-Jun Zhang, Shutao Zhang, Xiaotian Li, Xingqi Xia, Jiawei Lin, Zheyu Shen, Jiahang Chen, Qiuhao Xiong, Binran Wang, Fengyuan Wang, Ziyang Ni, Bohan Zhang, Fan Cui, Changkun Shao, Qing-Hong Cao, Ming-Xing Luo, Yaodong Yang, Muhan Zhang, Hua Xing Zhu
Current benchmarks for evaluating the reasoning capabilities of Large Language Models (LLMs) face significant limitations: task oversimplification, data contamination, and flawed evaluation items.
1 code implementation • CVPR 2025 • Runsong Zhu, Shi Qiu, Zhengzhe Liu, Ka-Hei Hui, Qianyi Wu, Pheng-Ann Heng, Chi-Wing Fu
Therefore, we formulate the association learning module and the noisy label filtering module for effective and robust codebook learning.
1 code implementation • 16 Mar 2025 • Zhiyu Liang, Dongrui Cai, Chenyuan Zhang, Zheng Liang, Chen Liang, Bo Zheng, Shi Qiu, Jin Wang, Hongzhi Wang
Model selection has been raised as an essential problem in the area of time series anomaly detection (TSAD), because there is no single best TSAD model for the highly heterogeneous time series in real-world applications.
no code implementations • 20 Feb 2025 • M-A-P Team, Xinrun Du, Yifan Yao, Kaijing Ma, Bingli Wang, Tianyu Zheng, King Zhu, Minghao Liu, Yiming Liang, Xiaolong Jin, Zhenlin Wei, Chujie Zheng, Kaixin Deng, Shawn Gavin, Shian Jia, Sichao Jiang, Yiyan Liao, Rui Li, Qinrui Li, Sirun Li, Yizhi Li, Yunwen Li, David Ma, Yuansheng Ni, Haoran Que, Qiyao Wang, Zhoufutu Wen, Siwei Wu, Tyshawn Hsing, Ming Xu, Zhenzhu Yang, Zekun Moore Wang, Junting Zhou, Yuelin Bai, Xingyuan Bu, Chenglin Cai, Liang Chen, Yifan Chen, Chengtuo Cheng, Tianhao Cheng, Keyi Ding, Siming Huang, Yun Huang, Yaoru Li, Yizhe Li, Zhaoqun Li, Tianhao Liang, Chengdong Lin, Hongquan Lin, Yinghao Ma, Tianyang Pang, Zhongyuan Peng, Zifan Peng, Qige Qi, Shi Qiu, Xingwei Qu, Shanghaoran Quan, Yizhou Tan, Zili Wang, Chenqing Wang, Hao Wang, Yiya Wang, YuBo Wang, Jiajun Xu, Kexin Yang, Ruibin Yuan, Yuanhao Yue, Tianyang Zhan, Chun Zhang, Jinyang Zhang, Xiyue Zhang, Xingjian Zhang, Yue Zhang, Yongchi Zhao, Xiangyu Zheng, Chenghua Zhong, Yang Gao, Zhoujun Li, Dayiheng Liu, Qian Liu, Tianyu Liu, Shiwen Ni, Junran Peng, Yujia Qin, Wenbo Su, Guoyin Wang, Shi Wang, Jian Yang, Min Yang, Meng Cao, Xiang Yue, Zhaoxiang Zhang, Wangchunshu Zhou, Jiaheng Liu, Qunshu Lin, Wenhao Huang, Ge Zhang
To address this gap, we present SuperGPQA, a comprehensive benchmark that evaluates graduate-level knowledge and reasoning capabilities across 285 disciplines.
no code implementations • 3 Feb 2025 • Haibo Tong, Zhaoyang Wang, Zhaorun Chen, Haonian Ji, Shi Qiu, Siwei Han, Kexin Geng, Zhongkai Xue, Yiyang Zhou, Peng Xia, Mingyu Ding, Rafael Rafailov, Chelsea Finn, Huaxiu Yao
Recent advancements in video generation have significantly improved the ability to synthesize videos from text instructions.
no code implementations • 16 Jan 2025 • Shi Qiu, Binzhu Xie, Qixuan Liu, Pheng-Ann Heng
3D Gaussian Splatting (3DGS) has recently emerged as an innovative and efficient 3D representation technique.
no code implementations • 12 Dec 2024 • Yuqi Tong, Yue Qiu, Ruiyang Li, Shi Qiu, Pheng-Ann Heng
We present MS2Mesh-XR, a novel multi-modal sketch-to-mesh generation pipeline that enables users to create realistic 3D objects in extended reality (XR) environments using hand-drawn sketches assisted by voice inputs.
no code implementations • 9 Dec 2024 • Shi Qiu, Binzhu Xie, Qixuan Liu, Pheng-Ann Heng
3D Gaussian Splatting (3DGS) has attracted significant attention for its potential to revolutionize 3D representation, rendering, and interaction.
1 code implementation • 26 Nov 2024 • Ruikai Cui, Shi Qiu, Jiawei Liu, Saeed Anwar, Nick Barnes
Recent advancements address this problem by training neural signed distance functions to pull 3D location queries to their closest points on a surface, following the predicted signed distances and the analytical gradients computed by the network.
1 code implementation • 14 Oct 2024 • Peng Xia, Siwei Han, Shi Qiu, Yiyang Zhou, Zhaoyang Wang, Wenhao Zheng, Zhaorun Chen, Chenhang Cui, Mingyu Ding, Linjie Li, Lijuan Wang, Huaxiu Yao
Extensive experiments demonstrate the effectiveness of our benchmark and metrics in providing a comprehensive evaluation of interleaved LVLMs.
1 code implementation • 14 Oct 2024 • Runsong Zhu, Shi Qiu, Qianyi Wu, Ka-Hei Hui, Pheng-Ann Heng, Chi-Wing Fu
Panoptic lifting is an effective technique to address the 3D panoptic segmentation task by unprojecting 2D panoptic segmentations from multi-views to 3D scene.
1 code implementation • CVPR 2024 • Tianhao Zhao, Yongcan Chen, Yu Wu, Tianyang Liu, Bo Du, Peilun Xiao, Shi Qiu, Hongda Yang, Guozhen Li, Yi Yang, Yutian Lin
In the first stage, we train a BEV autoencoder to reconstruct the BEV segmentation maps given corrupted noisy latent representation, which urges the decoder to learn fundamental knowledge of typical BEV patterns.
1 code implementation • 14 Sep 2023 • Wangchunshu Zhou, Yuchen Eleanor Jiang, Long Li, Jialong Wu, Tiannan Wang, Shi Qiu, Jintian Zhang, Jing Chen, Ruipu Wu, Shuai Wang, Shiding Zhu, Jiyu Chen, Wentao Zhang, Xiangru Tang, Ningyu Zhang, Huajun Chen, Peng Cui, Mrinmaya Sachan
Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language interfaces.
1 code implementation • 10 Aug 2023 • Ruikai Cui, Siyuan He, Shi Qiu
Foundation models, such as OpenAI's GPT-3 and GPT-4, Meta's LLaMA, and Google's PaLM2, have revolutionized the field of artificial intelligence.
1 code implementation • ICCV 2023 • Ruikai Cui, Shi Qiu, Saeed Anwar, Jiawei Liu, Chaoyue Xing, Jing Zhang, Nick Barnes
Point cloud completion aims to recover the complete shape based on a partial observation.
1 code implementation • 12 Jul 2023 • Humza Naveed, Asad Ullah Khan, Shi Qiu, Muhammad Saqib, Saeed Anwar, Muhammad Usman, Naveed Akhtar, Nick Barnes, Ajmal Mian
Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond.
1 code implementation • 5 Dec 2022 • Jie Hong, Shi Qiu, Weihao Li, Saeed Anwar, Mehrtash Harandi, Nick Barnes, Lars Petersson
Specifically, we use the Unknown-Point Simulator to simulate out-of-distribution data in the training stage by manipulating the geometric context of partial known data.
1 code implementation • 13 Nov 2022 • Ruikai Cui, Shi Qiu, Saeed Anwar, Jing Zhang, Nick Barnes
Unsupervised point cloud completion aims to infer the whole geometry of a partial object observation without requiring partial-complete correspondence.
no code implementations • 3 May 2022 • Chaojun Li, Shi Qiu
This study proposes an efficient algorithm for score computation for regime-switching models, and derived from which, an efficient expectation-maximization (EM) algorithm.
2 code implementations • 24 Nov 2021 • Shi Qiu, Saeed Anwar, Nick Barnes
Given the rapid development of 3D scanners, point clouds are becoming popular in AI-driven machines.
1 code implementation • 16 Aug 2021 • Shi Qiu, Saeed Anwar, Nick Barnes
With the help of the deep learning paradigm, many point cloud networks have been invented for visual analysis.
1 code implementation • 2 Aug 2021 • Shi Qiu, Yunfan Wu, Saeed Anwar, Chongyi Li
Object detection in three-dimensional (3D) space attracts much interest from academia and industry since it is an essential task in AI-driven applications such as robotics, autonomous driving, and augmented reality.
2 code implementations • CVPR 2021 • Shi Qiu, Saeed Anwar, Nick Barnes
Given the prominence of current 3D sensors, a fine-grained analysis on the basic point cloud data is worthy of further investigation.
Ranked #6 on
Semantic Segmentation
on Semantic3D
1 code implementation • 14 May 2020 • Shi Qiu, Saeed Anwar, Nick Barnes
Our DRNet is designed to learn local point features from the point cloud in different resolutions.
Ranked #25 on
3D Part Segmentation
on ShapeNet-Part
2 code implementations • 28 Nov 2019 • Shi Qiu, Saeed Anwar, Nick Barnes
As the basic task of point cloud analysis, classification is fundamental but always challenging.
Ranked #39 on
3D Point Cloud Classification
on ModelNet40
2 code implementations • 7 Aug 2017 • Sijie Yan, Ziwei Liu, Ping Luo, Shi Qiu, Xiaogang Wang, Xiaoou Tang
This work addresses unconstrained fashion landmark detection, where clothing bounding boxes are not provided in both training and test.
no code implementations • CVPR 2016 • Ziwei Liu, Ping Luo, Shi Qiu, Xiaogang Wang, Xiaoou Tang
To demonstrate the advantages of DeepFashion, we propose a new deep model, namely FashionNet, which learns clothing features by jointly predicting clothing attributes and landmarks.
Ranked #1 on
2D Cyclist Detection
on ^(#$!@#$)(()))******
(using extra training data)
no code implementations • CVPR 2015 • Wanli Ouyang, Xiaogang Wang, Xingyu Zeng, Shi Qiu, Ping Luo, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Chen-Change Loy, Xiaoou Tang
In this paper, we propose deformable deep convolutional neural networks for generic object detection.
no code implementations • 11 Sep 2014 • Wanli Ouyang, Ping Luo, Xingyu Zeng, Shi Qiu, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Yuanjun Xiong, Chen Qian, Zhenyao Zhu, Ruohui Wang, Chen-Change Loy, Xiaogang Wang, Xiaoou Tang
In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty.