722 citations · 5.1k across the 126 of their papers we have counts for
9 papers · 1 filter
Learning to Act Properly: Predicting and Explaining Affordances from Images
Ching-Yao Chuang, Jiaman Li, Antonio Torralba +1
We address the problem of affordance reasoning in diverse scenes that appear in the real world. Affordances relate the agent's actions to their effects when taken on the surroundin…
MovieGraphs: Towards Understanding Human-Centric Situations from Videos
Paul Vicol, Makarand Tapaswi, Lluis Castrejon +1
There is growing interest in artificial intelligence to build socially intelligent robots. This requires machines to have the ability to "read" people's emotions, motivations, and…
Be Your Own Prada: Fashion Synthesis with Structural Coherence
Shizhan Zhu, Sanja Fidler, Raquel Urtasun +2
We present a novel and effective approach for generating new clothing on a wearer through generative adversarial learning. Given an input image of a person and a sentence describin…
Situation Recognition with Graph Neural Networks
Ruiyu Li, Makarand Tapaswi, Renjie Liao +3
We address the problem of recognizing situations in images. Given an image, the task is to predict the most salient verb (action), and fill its semantic roles such as who is perfor…
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
Fartash Faghri, David J. Fleet, Jamie Ryan Kiros +1
We present a new technique for learning visual-semantic embeddings for cross-modal retrieval. Inspired by hard negative mining, the use of hard negatives in structured prediction,…
Teaching Machines to Describe Images via Natural Language Feedback
Huan Ling, Sanja Fidler
Robots will eventually be part of every household. It is thus critical to enable algorithms to learn from and be guided by non-expert users. In this paper, we bring a human in the…
Annotating Object Instances with a Polygon-RNN
Lluis Castrejon, Kaustav Kundu, Raquel Urtasun +1
We propose an approach for semi-automatic annotation of object instances. While most current methods treat object segmentation as a pixel-labeling problem, we here cast it as a pol…
Open Vocabulary Scene Parsing
Hang Zhao, Xavier Puig, Bolei Zhou +2
Recognizing arbitrary objects in the wild has been a challenging problem due to the limitations of existing classification models and datasets. In this paper, we propose a new task…
Towards Diverse and Natural Image Descriptions via a Conditional GAN
Bo Dai, Sanja Fidler, Raquel Urtasun +1
Despite the substantial progress in recent years, the image captioning techniques are still far from being perfect.Sentences produced by existing methods, e.g. those based on RNNs,…