310 citations · 1.2k across the 64 of their papers we have counts for
12 papers · 1 filter
Walking on Thin Air: Environment-Free Physics-based Markerless Motion Capture
Micha Livne, Leonid Sigal, Marcus A. Brubaker +1
We propose a generative approach to physics-based motion capture. Unlike prior attempts to incorporate physics into tracking that assume the subject and scene geometry are calibrat…
Traversing the Continuous Spectrum of Image Retrieval with Deep Dynamic Models
Ziad Al-Halah, Andreas M. Lehrmann, Leonid Sigal
We introduce the first work to tackle the image retrieval problem as a continuous operation. While the proposed approaches in the literature can be roughly categorized into two mai…
Image Generation from Layout
Bo Zhao, Lili Meng, Weidong Yin +1
Despite significant recent progress on generative models, controlled generation of images depicting multiple and complex object layouts is still a difficult problem. Among the core…
Middle-Out Decoding
Shikib Mehri, Leonid Sigal
Despite being virtually ubiquitous, sequence-to-sequence models are challenged by their lack of diversity and inability to be externally controlled. In this paper, we speculate tha…
Learning the Compositional Spaces for Generalized Zero-shot Learning
Hanze Dong, Yanwei Fu, Sung Ju Hwang +2
This paper studies the problem of Generalized Zero-shot Learning (G-ZSL), whose goal is to classify instances belonging to both seen and unseen classes at the test time. We propose…
Interpretable Spatio-temporal Attention for Video Action Recognition
Lili Meng, Bo Zhao, Bo Chang +4
Inspired by the observation that humans are able to process videos efficiently by only paying attention where and when it is needed, we propose an interpretable and easy plug-in sp…
Modular Generative Adversarial Networks
Bo Zhao, Bo Chang, Zequn Jie +1
Existing methods for multi-domain image-to-image translation (or generation) attempt to directly map an input image (or a random vector) to an image in one of the output domains. H…
A Neural Multi-sequence Alignment TeCHnique (NeuMATCH)
Pelin Dogan, Boyang Li, Leonid Sigal +1
The alignment of heterogeneous sequential data (video to text) is an important and challenging problem. Standard techniques for this task, including Dynamic Time Warping (DTW) and…
Multi-level Semantic Feature Augmentation for One-shot Learning
Zitian Chen, Yanwei Fu, Yinda Zhang +3
The ability to quickly recognize and learn new visual concepts from limited samples enables humans to swiftly adapt to new environments. This ability is enabled by semantic associa…
Multilevel Language and Vision Integration for Text-to-Clip Retrieval
Huijuan Xu, Kun He, Bryan A. Plummer +3
We address the problem of text-based activity retrieval in video. Given a sentence describing an activity, our task is to retrieve matching clips from an untrimmed video. To captur…
Probabilistic Video Generation using Holistic Attribute Control
Jiawei He, Andreas Lehrmann, Joseph Marino +2
Videos express highly structured spatio-temporal patterns of visual data. A video can be thought of as being governed by two factors: (i) temporally invariant (e.g., person identit…
Joint Event Detection and Description in Continuous Video Streams
Huijuan Xu, Boyang Li, Vasili Ramanishka +2
Dense video captioning is a fine-grained video understanding task that involves two sub-problems: localizing distinct events in a long video stream, and generating captions for the…