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Found 15 papers, 8 papers with code
Predicting masked tokens in stochastic locations improves masked image modeling
Specifically, we condition the model on stochastic masked token positions to guide the model toward learning features that are more robust to location uncertainties.
A Cookbook of Self-Supervised Learning
Self-supervised learning, dubbed the dark matter of intelligence, is a promising path to advance machine learning.
Visual Prompting via Image Inpainting
How does one adapt a pre-trained visual model to novel downstream tasks without task-specific finetuning or any model modification?
Ranked #5 on
Personalized Segmentation
on PerSeg
Structured Video Tokens @ Ego4D PNR Temporal Localization Challenge 2022
First, as both images and videos contain structured information, we enrich a transformer model with a set of \emph{object tokens} that can be used across images and videos.
Point- of-no-return (PNR) temporal localization
Temporal Localization
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens
We explore a particular instantiation of scene structure, namely a \emph{Hand-Object Graph}, consisting of hands and objects with their locations as nodes, and physical relations of contact/no-contact as edges.
Object-Region Video Transformers
In this work, we present Object-Region Video Transformers (ORViT), an \emph{object-centric} approach that extends video transformer layers with a block that directly incorporates object representations.
Ranked #3 on
Action Recognition
on Diving-48
DETReg: Unsupervised Pretraining with Region Priors for Object Detection
Recent self-supervised pretraining methods for object detection largely focus on pretraining the backbone of the object detector, neglecting key parts of detection architecture.
Ranked #1 on
Few-Shot Object Detection
on MS-COCO (10-shot)
3D Convolutional Sequence to Sequence Model for Vertebral Compression Fractures Identification in CT
An osteoporosis-related fracture occurs every three seconds worldwide, affecting one in three women and one in five men aged over 50.
Compositional Video Synthesis with Action Graphs
Our generative model for this task (AG2Vid) disentangles motion and appearance features, and by incorporating a scheduling mechanism for actions facilitates a timely and coordinated video generation.
Learning Canonical Representations for Scene Graph to Image Generation
Generating realistic images of complex visual scenes becomes challenging when one wishes to control the structure of the generated images.
Ranked #3 on
Layout-to-Image Generation
on Visual Genome 256x256
Improved ICH classification using task-dependent learning
Head CT is one of the most commonly performed imaging studied in the Emergency Department setting and Intracranial hemorrhage (ICH) is among the most critical and timesensitive findings to be detected on Head CT. We present BloodNet, a deep learning architecture designed for optimal triaging of Head CTs, with the goal of decreasing the time from CT acquisition to accurate ICH detection.
Learning Individual Styles of Conversational Gesture
Specifically, we perform cross-modal translation from "in-the-wild'' monologue speech of a single speaker to their hand and arm motion.
Ranked #4 on
Gesture Generation
on BEAT
PHT-bot: Deep-Learning based system for automatic risk stratification of COPD patients based upon signs of Pulmonary Hypertension
Secondary pulmonary hypertension is a manifestation of advanced COPD, which can be reliably diagnosed by the main Pulmonary Artery (PA) to Ascending Aorta (Ao) ratio.
Compression Fractures Detection on CT
Finally a Recurrent Neural Network (RNN) is utilized to predict whether a vertebral fracture is present in the series of patches.
Language Generation with Recurrent Generative Adversarial Networks without Pre-training
Generative Adversarial Networks (GANs) have shown great promise recently in image generation.
