Search Results for author:
Found 15 papers, 5 papers with code
Sketch-guided Image Inpainting with Partial Discrete Diffusion Process
In this work, we study the task of sketch-guided image inpainting.
Towards Scene-Text to Scene-Text Translation
In this work, we study the task of ``visually" translating scene text from a source language (e. g., English) to a target language (e. g., Chinese).
Answer Mining from a Pool of Images: Towards Retrieval-Based Visual Question Answering
We study visual question answering in a setting where the answer has to be mined from a pool of relevant and irrelevant images given as a context.
Query-guided Attention in Vision Transformers for Localizing Objects Using a Single Sketch
and Sketchy datasets, respectively, and a $12. 2\%$ improvement in AP@50 for large objects that are `unseen' during training.
Few-Shot Referring Relationships in Videos
Given a query visual relationship as <subject, predicate, object> and a test video, our objective is to localize the subject and object that are connected via the predicate.
Multimodal Query-guided Object Localization
In such a scenario, a hand-drawn sketch of the object could be a choice for a query.
Contrastive Multi-View Textual-Visual Encoding: Towards One Hundred Thousand-Scale One-Shot Logo Identification
To fill this gap in the literature, we introduce Wikidata Reference Logo Dataset (WiRLD), containing logos for 100K business brands harvested from Wikidata.
Look, Read and Ask: Learning to Ask Questions by Reading Text in Images
However, it is challenging as it requires an in-depth understanding of the scene and the ability to semantically bridge the visual content with the text present in the image.
Grounding Scene Graphs on Natural Images via Visio-Lingual Message Passing
In VL-MPAG Net, we first construct a directed graph with object proposals as nodes and an edge between a pair of nodes representing a plausible relation between them.
COFAR: Commonsense and Factual Reasoning in Image Search
To enable both commonsense and factual reasoning in the image search, we present a unified framework, namely Knowledge Retrieval-Augmented Multimodal Transformer (KRAMT), that treats the named visual entities in an image as a gateway to encyclopedic knowledge and leverages them along with natural language query to ground relevant knowledge.
Few-shot Visual Relationship Co-localization
In this paper, given a small bag of images, each containing a common but latent predicate, we are interested in localizing visual subject-object pairs connected via the common predicate in each of the images.
Sketch-Guided Object Localization in Natural Images
We refer to this problem as sketch-guided object localization.
Deep Embedding using Bayesian Risk Minimization with Application to Sketch Recognition
In this paper, we address the problem of hand-drawn sketch recognition.
Enhancing Energy Minimization Framework for Scene Text Recognition with Top-Down Cues
We build a conditional random field model on these detections to jointly model the strength of the detections and the interactions between them.
Scene Text Recognition using Higher Order Language Priors
The problem of recognizing text in images taken in the wild has gained significant attention from the computer vision community in recent years.
