Anelia Angelova

research

∙ 09/02/2023

Contrastive Feature Masking Open-Vocabulary Vision Transformer

We present Contrastive Feature Masking Vision Transformer (CFM-ViT) - an...

0 Dahun Kim, et al. ∙

research

∙ 06/06/2023

Diversifying Joint Vision-Language Tokenization Learning

Building joint representations across images and text is an essential st...

0 Vardaan Pahuja, et al. ∙

research

∙ 05/31/2023

Joint Adaptive Representations for Image-Language Learning

Image-language learning has made unprecedented progress in visual unders...

0 AJ Piergiovanni, et al. ∙

research

∙ 05/11/2023

Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers

We present Region-aware Open-vocabulary Vision Transformers (RO-ViT) - a...

0 Dahun Kim, et al. ∙

research

∙ 03/29/2023

MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks

The development of language models have moved from encoder-decoder to de...

0 Weicheng Kuo, et al. ∙

research

∙ 12/06/2022

Rethinking Video ViTs: Sparse Video Tubes for Joint Image and Video Learning

We present a simple approach which can turn a ViT encoder into an effici...

0 AJ Piergiovanni, et al. ∙

research

∙ 09/30/2022

F-VLM: Open-Vocabulary Object Detection upon Frozen Vision and Language Models

We present F-VLM, a simple open-vocabulary object detection method built...

0 Weicheng Kuo, et al. ∙

research

∙ 09/14/2022

PaLI: A Jointly-Scaled Multilingual Language-Image Model

Effective scaling and a flexible task interface enable large language mo...

6 Xi Chen, et al. ∙

research

∙ 09/09/2022

Pre-training image-language transformers for open-vocabulary tasks

We present a pre-training approach for vision and language transformer m...

0 AJ Piergiovanni, et al. ∙

research

∙ 08/01/2022

Video Question Answering with Iterative Video-Text Co-Tokenization

Video question answering is a challenging task that requires understandi...

0 AJ Piergiovanni, et al. ∙

research

∙ 07/05/2022

Mechanical Search on Shelves with Efficient Stacking and Destacking of Objects

Stacking increases storage efficiency in shelves, but the lack of visibi...

0 Huang Huang, et al. ∙

research

∙ 05/02/2022

Answer-Me: Multi-Task Open-Vocabulary Visual Question Answering

We present Answer-Me, a task-aware multi-task framework which unifies a ...

0 AJ Piergiovanni, et al. ∙

research

∙ 03/31/2022

FindIt: Generalized Localization with Natural Language Queries

We propose FindIt, a simple and versatile framework that unifies a varie...

0 Weicheng Kuo, et al. ∙

research

∙ 01/22/2022

Mechanical Search on Shelves using a Novel "Bluction" Tool

Shelves are common in homes, warehouses, and commercial settings due to ...

27 Huang Huang, et al. ∙

research

∙ 09/02/2021

4D-Net for Learned Multi-Modal Alignment

We present 4D-Net, a 3D object detection approach, which utilizes 3D Poi...

7 AJ Piergiovanni, et al. ∙

research

∙ 08/20/2021

Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Image

3D perception of object shapes from RGB image input is fundamental towar...

11 Weicheng Kuo, et al. ∙

research

∙ 08/15/2021

Learning Open-World Object Proposals without Learning to Classify

Object proposals have become an integral preprocessing steps of many vis...

11 Dahun Kim, et al. ∙

research

∙ 06/28/2021

Unsupervised Discovery of Actions in Instructional Videos

In this paper we address the problem of automatically discovering atomic...

10 AJ Piergiovanni, et al. ∙

research

∙ 06/21/2021

TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?

In this paper, we introduce a novel visual representation learning which...

0 Michael S. Ryoo, et al. ∙

research

∙ 06/07/2021

Unsupervised Action Segmentation for Instructional Videos

In this paper we address the problem of automatically discovering atomic...

0 AJ Piergiovanni, et al. ∙

research

∙ 05/14/2021

SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping

We present SMURF, a method for unsupervised learning of optical flow tha...

15 Austin Stone, et al. ∙

research

∙ 04/14/2021

Adaptive Intermediate Representations for Video Understanding

A common strategy to video understanding is to incorporate spatial and m...

0 Juhana Kangaspunta, et al. ∙

research

∙ 03/26/2021

Visionary: Vision architecture discovery for robot learning

We propose a vision-based architecture search algorithm for robot manipu...

0 Iretiayo Akinola, et al. ∙

research

∙ 11/23/2020

Mechanical Search on Shelves using Lateral Access X-RAY

Efficiently finding an occluded object with lateral access arises in man...

0 Huang Huang, et al. ∙

research

∙ 10/30/2020

Unsupervised Monocular Depth Learning in Dynamic Scenes

We present a method for jointly training the estimation of depth, ego-mo...

5 Hanhan Li, et al. ∙

research

∙ 08/18/2020

AssembleNet++: Assembling Modality Representations via Attention Connections

We create a family of powerful video models which are able to: (i) learn...

0 Michael S. Ryoo, et al. ∙

research

∙ 08/11/2020

Adversarial Generative Grammars for Human Activity Prediction

In this paper we propose an adversarial generative grammar model for fut...

15 AJ Piergiovanni, et al. ∙

research

∙ 07/26/2020

Mask2CAD: 3D Shape Prediction by Learning to Segment and Retrieve

Object recognition has seen significant progress in the image domain, wi...

0 Weicheng Kuo, et al. ∙

research

∙ 07/23/2020

AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification

Convolutional operations have two limitations: (1) do not explicitly mod...

10 Xiaofang Wang, et al. ∙

research

∙ 06/08/2020

What Matters in Unsupervised Optical Flow

We systematically compare and analyze a set of key components in unsuper...

7 Rico Jonschkowski, et al. ∙

research

∙ 05/19/2020

Differentiable Mapping Networks: Learning Structured Map Representations for Sparse Visual Localization

Mapping and localization, preferably from a small number of observations...

0 Peter Karkus, et al. ∙

research

∙ 05/14/2020

Taskology: Utilizing Task Relations at Scale

It has been recognized that the joint training of computer vision tasks ...

1 Yao Lu, et al. ∙

research

∙ 04/20/2020

X-Ray: Mechanical Search for an Occluded Object by Minimizing Support of Learned Occupancy Distributions

For applications in e-commerce, warehouses, healthcare, and home service...

2 Michael Danielczuk, et al. ∙

research

∙ 04/11/2020

Improving Semantic Segmentation through Spatio-Temporal Consistency Learned from Videos

We leverage unsupervised learning of depth, egomotion, and camera intrin...

0 Ankita Pasad, et al. ∙

research

∙ 02/26/2020

Evolving Losses for Unsupervised Video Representation Learning

We present a new method to learn video representations from large-scale ...

0 AJ Piergiovanni, et al. ∙

research

∙ 12/13/2019

SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong

We introduce a new high resolution, high frame rate stereo video dataset...

12 Steven Schwarcz, et al. ∙

research

∙ 12/05/2019

KeyPose: Multi-view 3D Labeling and Keypoint Estimation for Transparent Objects

Estimating the 3D pose of desktop objects is crucial for applications su...

5 Xingyu Liu, et al. ∙

research

∙ 10/15/2019

Tiny Video Networks

Video understanding is a challenging problem with great impact on the ab...

0 AJ Piergiovanni, et al. ∙

research

∙ 06/12/2019

Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics

We present an approach which takes advantage of both structure and seman...

6 Vincent Casser, et al. ∙

research

∙ 06/07/2019

Evolving Losses for Unlabeled Video Representation Learning

We present a new method to learn video representations from unlabeled da...

0 AJ Piergiovanni, et al. ∙

research

∙ 05/30/2019

AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures

Learning to represent videos is a very challenging task both algorithmic...

0 Michael S. Ryoo, et al. ∙

research

∙ 04/10/2019

Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras

We present a novel method for simultaneous learning of depth, egomotion,...

0 Ariel Gordon, et al. ∙

research

∙ 04/05/2019

ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors

Instance segmentation aims to detect and segment individual objects in a...

8 Weicheng Kuo, et al. ∙

research

∙ 02/01/2019

Learning Differentiable Grammars for Continuous Data

This paper proposes a novel algorithm which learns a formal regular gram...

0 AJ Piergiovanni, et al. ∙

research

∙ 11/28/2018

Future Segmentation Using 3D Structure

Predicting the future to anticipate the outcome of events and actions is...

0 Suhani Vora, et al. ∙

research

∙ 11/26/2018

Evolving Space-Time Neural Architectures for Videos

In this paper, we present a new method for evolving video CNN models to ...

2 AJ Piergiovanni, et al. ∙

research

∙ 11/15/2018

Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos

Learning to predict scene depth from RGB inputs is a challenging task bo...

30 Vincent Casser, et al. ∙

research

∙ 02/15/2018

Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

We present a novel approach for unsupervised learning of depth and ego-m...

0 Reza Mahjourian, et al. ∙

research

∙ 01/26/2018

Object category learning and retrieval with weak supervision

We consider the problem of retrieving objects from image data and learni...

0 Steven Hickson, et al. ∙

research

∙ 03/13/2017

Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs

We approach structured output prediction by optimizing a deep value netw...

0 Michael Gygli, et al. ∙

Anelia Angelova

Featured Co-authors