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Found 9 papers, 0 papers with code
Coarse-to-Fine Contrastive Learning in Image-Text-Graph Space for Improved Vision-Language Compositionality
Along with this, we propose novel negative mining techniques in the scene graph space for improving attribute binding and relation understanding.
Ranked #1 on
Image Retrieval
on CREPE (Compositional REPresentation Evaluation)
(Recall@1 (HN-Comp, UC) metric)
Que2Engage: Embedding-based Retrieval for Relevant and Engaging Products at Facebook Marketplace
In this paper we presents Que2Engage, a search EBR system built towards bridging the gap between retrieval and ranking for end-to-end optimizations.
FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning
Additionally, these works have mainly been restricted to multimodal understanding tasks.
LoopITR: Combining Dual and Cross Encoder Architectures for Image-Text Retrieval
In this work, we propose LoopITR, which combines them in the same network for joint learning.
Cryptocurrency Address Clustering and Labeling
Anonymity is one of the most important qualities of blockchain technology.
An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations
Several factors contribute to the appearance of an object in a visual scene, including pose, illumination, and deformation, among others.
Learning the Multilinear Structure of Visual Data
To extract these modes of variations from visual data, several supervised methods, such as the TensorFaces, that rely on multilinear (tensor) decomposition (e. g., Higher Order SVD) have been developed.
Multi-view (Joint) Probability Linear Discrimination Analysis for Multi-view Feature Verification
However, in practical use, when using multi-task learned network as feature extractor, the extracted feature are always attached to several labels.
