Skip to main navigation
Skip to search
Skip to main content
ÉTS Research Discovery Portal Home
Help & FAQ
Link opens in a new tab
Français
English
Search content at ÉTS Research Discovery Portal
Home
Profiles
Research units
Projects
Research output
Datasets
Press/Media
Student theses
TeD-Loc: Text distillation for weakly supervised object localization
Shakeeb Murtaza
, Soufiane Belharbi
, Alexis Guichemerre
,
Marco Pedersoli
,
Eric Granger
École de technologie supérieure
Systems Engineering Department
LIVIA - Imaging, Vision and Artificial Intelligence Laboratory
itechsanté - Research Institute for Innovation in Health Technologies
École de technologie supérieure
Research output
:
Contribution to journal
›
Journal Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'TeD-Loc: Text distillation for weakly supervised object localization'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Weakly Supervised Object Localization
100%
Distillation
100%
Patch Embedding
60%
Text Embedding
40%
Patch Level
40%
Single Model
20%
Denoising
20%
Localization Model
20%
Local Patch
20%
Object Class
20%
Classification Module
20%
Learning Strategies
20%
Bounding Box Annotation
20%
ILSVRC
20%
Orthogonalization
20%
Prompt Learning
20%
Class Activation Map
20%
Class Token
20%
Object Region
20%
Efficient Inference
20%
Foreground-background
20%
Global Classes
20%
Spatial Regions
20%
Histopathology
20%
Knowledge Distillation
20%
Localization Method
20%
Localization Rate
20%
Joint Classification
20%
Contrastive Alignment
20%
Joint Localization
20%
Similarity Classes
20%
Semantic Prior
20%
Token Embeddings
20%
Global Text
20%
Rich Semantics
20%
Computer Science
Annotation
100%
de-noising
100%
localization algorithm
100%
Orthogonalization
100%
Class Activation Mapping
100%
Spatial Extent
100%
Prompt Learning
100%