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Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual
  Representation Learning

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning

7 January 2019
Baoyuan Wu
Weidong Chen
Yanbo Fan
Yong Zhang
Jinlong Hou
Jie Liu
Tong Zhang
    VLM
    MLLM
ArXivPDFHTML

Papers citing "Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning"

14 / 14 papers shown
Title
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
Andy Zeng
Maria Attarian
Brian Ichter
K. Choromanski
Adrian S. Wong
...
Michael S. Ryoo
Vikas Sindhwani
Johnny Lee
Vincent Vanhoucke
Peter R. Florence
ReLM
LRM
49
574
0
01 Apr 2022
REFLACX, a dataset of reports and eye-tracking data for localization of
  abnormalities in chest x-rays
REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rays
Ricardo Bigolin Lanfredi
Mingyuan Zhang
W. Auffermann
Jessica Chan
Phuong-Anh T. Duong
Vivek Srikumar
Trafton Drew
Joyce D. Schroeder
Tolga Tasdizen
18
40
0
29 Sep 2021
PASS: An ImageNet replacement for self-supervised pretraining without
  humans
PASS: An ImageNet replacement for self-supervised pretraining without humans
Yuki M. Asano
Christian Rupprecht
Andrew Zisserman
Andrea Vedaldi
VLM
SSL
26
57
0
27 Sep 2021
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel
  Classification
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification
Gabriel Bénédict
Vincent Koops
Daan Odijk
Maarten de Rijke
37
30
0
24 Aug 2021
Multi-Label Learning from Single Positive Labels
Multi-Label Learning from Single Positive Labels
Elijah Cole
Oisin Mac Aodha
Titouan Lorieul
Pietro Perona
Dan Morris
Nebojsa Jojic
23
108
0
17 Jun 2021
Sewer-ML: A Multi-Label Sewer Defect Classification Dataset and
  Benchmark
Sewer-ML: A Multi-Label Sewer Defect Classification Dataset and Benchmark
Joakim Bruslund Haurum
T. Moeslund
20
60
0
19 Mar 2021
The Emerging Trends of Multi-Label Learning
The Emerging Trends of Multi-Label Learning
Weiwei Liu
Haobo Wang
Xiaobo Shen
Ivor W. Tsang
40
252
0
23 Nov 2020
Webly Supervised Image Classification with Metadata: Automatic Noisy
  Label Correction via Visual-Semantic Graph
Webly Supervised Image Classification with Metadata: Automatic Noisy Label Correction via Visual-Semantic Graph
Jingkang Yang
Weirong Chen
Xue Jiang
Xiaopeng Yan
Huabin Zheng
Wayne Zhang
NoLa
33
13
0
12 Oct 2020
Measuring Robustness to Natural Distribution Shifts in Image
  Classification
Measuring Robustness to Natural Distribution Shifts in Image Classification
Rohan Taori
Achal Dave
Vaishaal Shankar
Nicholas Carlini
Benjamin Recht
Ludwig Schmidt
OOD
48
536
0
01 Jul 2020
Towards Crowdsourced Training of Large Neural Networks using
  Decentralized Mixture-of-Experts
Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts
Max Ryabinin
Anton I. Gusev
FedML
27
48
0
10 Feb 2020
Scaling Out-of-Distribution Detection for Real-World Settings
Scaling Out-of-Distribution Detection for Real-World Settings
Dan Hendrycks
Steven Basart
Mantas Mazeika
Andy Zou
Joe Kwon
Mohammadreza Mostajabi
Jacob Steinhardt
D. Song
OODD
20
463
0
25 Nov 2019
Does Object Recognition Work for Everyone?
Does Object Recognition Work for Everyone?
Terrance Devries
Ishan Misra
Changhan Wang
Laurens van der Maaten
45
262
0
06 Jun 2019
Air Learning: A Deep Reinforcement Learning Gym for Autonomous Aerial
  Robot Visual Navigation
Air Learning: A Deep Reinforcement Learning Gym for Autonomous Aerial Robot Visual Navigation
Srivatsan Krishnan
Behzad Boroujerdian
William Fu
Aleksandra Faust
Vijay Janapa Reddi
16
36
0
02 Jun 2019
Deep Learning on Small Datasets without Pre-Training using Cosine Loss
Deep Learning on Small Datasets without Pre-Training using Cosine Loss
Björn Barz
Joachim Denzler
27
129
0
25 Jan 2019
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