activity
20182021
most citedContext-Aware Embeddings for Automatic Art Analysis

56 citations · 145 across the 12 of their papers we have counts for

collaborators

21 papers

cs.LG20214 cited

GCNBoost: Artwork Classification by Label Propagation through a Knowledge Graph

Cheikh Brahim El Vaigh, Noa Garcia, Benjamin Renoust +3

The rise of digitization of cultural documents offers large-scale contents, opening the road for development of AI systems in order to preserve, search, and deliver cultural herita…

cs.CV202122 cited

Understanding the Role of Scene Graphs in Visual Question Answering

Vinay Damodaran, Sharanya Chakravarthy, Akshay Kumar +5

Visual Question Answering (VQA) is of tremendous interest to the research community with important applications such as aiding visually impaired users and image-based search. In th…

cs.CV20201 cited

Match Them Up: Visually Explainable Few-shot Image Classification

Bowen Wang, Liangzhi Li, Manisha Verma +3

Few-shot learning (FSL) approaches are usually based on an assumption that the pre-trained knowledge can be obtained from base (seen) categories and can be well transferred to nove…

cs.CV2020

Noisy-LSTM: Improving Temporal Awareness for Video Semantic Segmentation

Bowen Wang, Liangzhi Li, Yuta Nakashima +3

Semantic video segmentation is a key challenge for various applications. This paper presents a new model named Noisy-LSTM, which is trainable in an end-to-end manner, with convolut…

cs.CV2020

Constructing a Visual Relationship Authenticity Dataset

Chenhui Chu, Yuto Takebayashi, Mishra Vipul +1

A visual relationship denotes a relationship between two objects in an image, which can be represented as a triplet of (subject; predicate; object). Visual relationship detection i…

cs.CV2020

Uncovering Hidden Challenges in Query-Based Video Moment Retrieval

Mayu Otani, Yuta Nakashima, Esa Rahtu +1

The query-based moment retrieval is a problem of localising a specific clip from an untrimmed video according a query sentence. This is a challenging task that requires interpretat…