Search Results for author: Shi Qiu

Found 17 papers, 12 papers with code

Agents: An Open-source Framework for Autonomous Language Agents

1 code implementation14 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, 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.

Adaptive Low Rank Adaptation of Segment Anything to Salient Object Detection

no code implementations10 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.

object-detection Object Detection +2

A Comprehensive Overview of Large Language Models

1 code implementation12 Jul 2023 Humza Naveed, Asad Ullah Khan, Shi Qiu, Muhammad Saqib, Saeed Anwar, Muhammad Usman, Naveed Akhtar, Nick Barnes, Ajmal Mian

Considering the rapidly emerging plethora of literature on LLMs, it is imperative that the research community is able to benefit from a concise yet comprehensive overview of the recent developments in this field.


PointCaM: Cut-and-Mix for Open-Set Point Cloud Learning

1 code implementation5 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.

Energy-Based Residual Latent Transport for Unsupervised Point Cloud Completion

1 code implementation13 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.

Point Cloud Completion

Efficient Score Computation and Expectation-Maximization Algorithm in Regime-Switching Models

no code implementations3 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.

PU-Transformer: Point Cloud Upsampling Transformer

2 code implementations24 Nov 2021 Shi Qiu, Saeed Anwar, Nick Barnes

Given the rapid development of 3D scanners, point clouds are becoming popular in AI-driven machines.

PnP-3D: A Plug-and-Play for 3D Point Clouds

1 code implementation16 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.

object-detection Object Detection +1

Investigating Attention Mechanism in 3D Point Cloud Object Detection

1 code implementation2 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.

Autonomous Driving object-detection +1

Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion

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.

3D Semantic Segmentation

Unconstrained Fashion Landmark Detection via Hierarchical Recurrent Transformer Networks

2 code implementations7 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.

DeepFashion: Powering Robust Clothes Recognition and Retrieval With Rich Annotations

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.


DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection

no code implementations11 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.

object-detection Object Detection

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