Search Results for author:
Found 15 papers, 3 papers with code
DocTr: Document Transformer for Structured Information Extraction in Documents
We present a new formulation for structured information extraction (SIE) from visually rich documents.
Ranked #2 on
Entity Linking
on FUNSD
Object-Aware Cropping for Self-Supervised Learning
This assumption is mostly satisfied in datasets such as ImageNet where there is a large, centered object, which is highly likely to be present in random crops of the full image.
Learning Visual Representations for Transfer Learning by Suppressing Texture
Recent literature has shown that features obtained from supervised training of CNNs may over-emphasize texture rather than encoding high-level information.
Ranked #19 on
Object Detection
on PASCAL VOC 2007
Pose And Joint-Aware Action Recognition
Unlike other modalities, constellation of joints and their motion generate models with succinct human motion information for activity recognition.
Ranked #1 on
Action Recognition
on Mimetics
Visual Question Answering on Image Sets
To enable research in this new topic, we introduce two ISVQA datasets - indoor and outdoor scenes.
Spatial Priming for Detecting Human-Object Interactions
The proposed method consists of a layout module which primes a visual module to predict the type of interaction between a human and an object.
How are attributes expressed in face DCNNs?
In the final fully connected layer of the networks, we found the order of expressivity for facial attributes to be Age > Sex > Yaw.
Detecting Human-Object Interactions via Functional Generalization
We present an approach for detecting human-object interactions (HOIs) in images, based on the idea that humans interact with functionally similar objects in a similar manner.
A Fast and Accurate System for Face Detection, Identification, and Verification
We provide evaluation results of the proposed face detector on challenging unconstrained face detection datasets.
Zero-Shot Object Detection
We introduce and tackle the problem of zero-shot object detection (ZSD), which aims to detect object classes which are not observed during training.
Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition
We show that integrating this simple step in the training pipeline significantly improves the performance of face verification and recognition systems.
UPSET and ANGRI : Breaking High Performance Image Classifiers
In this paper, targeted fooling of high performance image classifiers is achieved by developing two novel attack methods.
The Do's and Don'ts for CNN-based Face Verification
While the research community appears to have developed a consensus on the methods of acquiring annotated data, design and training of CNNs, many questions still remain to be answered.
UMDFaces: An Annotated Face Dataset for Training Deep Networks
Recent progress in face detection (including keypoint detection), and recognition is mainly being driven by (i) deeper convolutional neural network architectures, and (ii) larger datasets.
People Counting in High Density Crowds from Still Images
The method estimates counts by fusing information from multiple sources.
