42 citations · 156 across the 26 of their papers we have counts for
30 papers
Single-Stage Visual Relationship Learning using Conditional Queries
Alakh Desai, Tz-Ying Wu, Subarna Tripathi +1
Research in scene graph generation (SGG) usually considers two-stage models, that is, detecting a set of entities, followed by combining them and labeling all possible relationship…
SViTT: Temporal Learning of Sparse Video-Text Transformers
Yi Li, Kyle Min, Subarna Tripathi +1
Do video-text transformers learn to model temporal relationships across frames? Despite their immense capacity and the abundance of multimodal training data, recent work has reveal…
Unbiased Scene Graph Generation in Videos
Sayak Nag, Kyle Min, Subarna Tripathi +1
The task of dynamic scene graph generation (SGG) from videos is complicated and challenging due to the inherent dynamics of a scene, temporal fluctuation of model predictions, and…
Learning Long-Term Spatial-Temporal Graphs for Active Speaker Detection
Kyle Min, Sourya Roy, Subarna Tripathi +2
Active speaker detection (ASD) in videos with multiple speakers is a challenging task as it requires learning effective audiovisual features and spatial-temporal correlations over…
EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting
Ethan Jacob Moyer, Alisha Isabelle Augustin, Satvik Tripathi +5
In this work, we highlight our novel evolutionary sparse time-series forecasting algorithm also known as EvoSTS. The algorithm attempts to evolutionary prioritize weights of Long S…
Text Spotting Transformers
Xiang Zhang, Yongwen Su, Subarna Tripathi +1
In this paper, we present TExt Spotting TRansformers (TESTR), a generic end-to-end text spotting framework using Transformers for text detection and recognition in the wild. TESTR…
Joint Hand Motion and Interaction Hotspots Prediction from Egocentric Videos
Shaowei Liu, Subarna Tripathi, Somdeb Majumdar +1
We propose to forecast future hand-object interactions given an egocentric video. Instead of predicting action labels or pixels, we directly predict the hand motion trajectory and…
Learning Spatial-Temporal Graphs for Active Speaker Detection
Sourya Roy, Kyle Min, Subarna Tripathi +2
We address the problem of active speaker detection through a new framework, called SPELL, that learns long-range multimodal graphs to encode the inter-modal relationship between au…
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs
Shengyu Feng, Subarna Tripathi, Hesham Mostafa +2
Dynamic scene graph generation from a video is challenging due to the temporal dynamics of the scene and the inherent temporal fluctuations of predictions. We hypothesize that capt…
Towards Panoptic 3D Parsing for Single Image in the Wild
Sainan Liu, Vincent Nguyen, Yuan Gao +2
Performing single image holistic understanding and 3D reconstruction is a central task in computer vision. This paper presents an integrated system that performs dense scene labeli…
Early Diagnostic Prediction of Covid-19 using Gradient-Boosting Machine Model
Satvik Tripathi
With the huge spike in the COVID-19 cases across the globe and reverse transcriptase-polymerase chain reaction (RT-PCR) test remains a key component for rapid and accurate detectio…
Learning of Visual Relations: The Devil is in the Tails
Alakh Desai, Tz-Ying Wu, Subarna Tripathi +1
Significant effort has been recently devoted to modeling visual relations. This has mostly addressed the design of architectures, typically by adding parameters and increasing mode…
In Defense of Scene Graphs for Image Captioning
Kien Nguyen, Subarna Tripathi, Bang Du +2
The mainstream image captioning models rely on Convolutional Neural Network (CNN) image features to generate captions via recurrent models. Recently, image scene graphs have been u…
Structured Query-Based Image Retrieval Using Scene Graphs
Brigit Schroeder, Subarna Tripathi
A structured query can capture the complexity of object interactions (e.g. 'woman rides motorcycle') unlike single objects (e.g. 'woman' or 'motorcycle'). Retrieval using structure…
Triplet-Aware Scene Graph Embeddings
Brigit Schroeder, Subarna Tripathi, Hanlin Tang
Scene graphs have become an important form of structured knowledge for tasks such as for image generation, visual relation detection, visual question answering, and image retrieval…
Compact Scene Graphs for Layout Composition and Patch Retrieval
Subarna Tripathi, Sharath Nittur Sridhar, Sairam Sundaresan +1
Structured representations such as scene graphs serve as an efficient and compact representation that can be used for downstream rendering or retrieval tasks. However, existing eff…
Toward Joint Image Generation and Compression using Generative Adversarial Networks
Byeongkeun Kang, Subarna Tripathi, Truong Q. Nguyen
In this paper, we present a generative adversarial network framework that generates compressed images instead of synthesizing raw RGB images and compressing them separately. In the…
Using Scene Graph Context to Improve Image Generation
Subarna Tripathi, Anahita Bhiwandiwalla, Alexei Bastidas +1
Generating realistic images from scene graphs asks neural networks to be able to reason about object relationships and compositionality. As a relatively new task, how to properly e…
PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding
Kaichun Mo, Shilin Zhu, Angel X. Chang +4
We present PartNet: a consistent, large-scale dataset of 3D objects annotated with fine-grained, instance-level, and hierarchical 3D part information. Our dataset consists of 573,5…
Correction by Projection: Denoising Images with Generative Adversarial Networks
Subarna Tripathi, Zachary C. Lipton, Truong Q. Nguyen
Generative adversarial networks (GANs) transform low-dimensional latent vectors into visually plausible images. If the real dataset contains only clean images, then ostensibly, the…
LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems
Subarna Tripathi, Gokce Dane, Byeongkeun Kang +2
Deep convolutional Neural Networks (CNN) are the state-of-the-art performers for object detection task. It is well known that object detection requires more computation and memory…
Pose2Instance: Harnessing Keypoints for Person Instance Segmentation
Subarna Tripathi, Maxwell Collins, Matthew Brown +1
Human keypoints are a well-studied representation of people.We explore how to use keypoint models to improve instance-level person segmentation. The main idea is to harness the not…
A Statistical Approach to Continuous Self-Calibrating Eye Gaze Tracking for Head-Mounted Virtual Reality Systems
Subarna Tripathi, Brian Guenter
We present a novel, automatic eye gaze tracking scheme inspired by smooth pursuit eye motion while playing mobile games or watching virtual reality contents. Our algorithm continuo…
Context Matters: Refining Object Detection in Video with Recurrent Neural Networks
Subarna Tripathi, Zachary C. Lipton, Serge Belongie +1
Given the vast amounts of video available online, and recent breakthroughs in object detection with static images, object detection in video offers a promising new frontier. Howeve…