Search Results for author:
Found 7 papers, 2 papers with code
Learning and Verification of Task Structure in Instructional Videos
We introduce a new pre-trained video model, VideoTaskformer, focused on representing the semantics and structure of instructional videos.
RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
Semi-supervised learning aims to train a model using limited labels.
Tell Me What Happened: Unifying Text-guided Video Completion via Multimodal Masked Video Generation
Inspired by this, we introduce a novel task, text-guided video completion (TVC), which requests the model to generate a video from partial frames guided by an instruction.
Ranked #3 on
Video Prediction
on BAIR Robot Pushing
Shading Annotations in the Wild
We demonstrate the value of our data and network in an application to intrinsic images, where we can reduce decomposition artifacts produced by existing algorithms.
Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks
In this paper we present the Inside-Outside Net (ION), an object detector that exploits information both inside and outside the region of interest.
Ranked #224 on
Object Detection
on COCO test-dev
Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences
In this paper, we propose a novel learning framework to help answer these types of questions.
Material Recognition in the Wild with the Materials in Context Database
In this paper, we introduce a new, large-scale, open dataset of materials in the wild, the Materials in Context Database (MINC), and combine this dataset with deep learning to achieve material recognition and segmentation of images in the wild.
