I am a Ph.D. student at MIT. My research studies computer vision and machine learning.
There is an abundance of unlabeled data available to us that contain rich signals about the world. We hope to leverage this resource to expand the capabilities of visual models.
Anticipating Visual Representations with Unlabeled Video
Carl Vondrick, Hamed Pirsiavash, Antonio Torralba
Predicting Motivations of Actions by Leveraging Text
Carl Vondrick, Deniz Oktay, Hamed Pirsiavash, Antonio Torralba
Learning Aligned Cross-Modal Representations from Weakly Aligned Data
Lluis Castrejon*, Yusuf Aytar*, Carl Vondrick, Hamed Pirsiavash, Antonio Torralba
The ability to understand what other people do is crucial in our everyday life. We are interested in developing visual models for machines to reason about people's activities.
Where are they looking?
Adria Recasens*, Aditya Khosla*, Carl Vondrick, Antonio Torralba
Assessing the Quality of Actions
Hamed Pirsiavash, Carl Vondrick, Antonio Torralba
In order to improve upon computer vision models, it is instructive to first understand and diagnose their failures. We are interested in methods to analyze and visualize what computer vision models have learned.
Visualizing Object Detection Features
Carl Vondrick, Aditya Khosla, Hamed Pirsiavash, Tomasz Malisiewicz, Antonio Torralba
Do We Need More Training Data?
Xiangxin Zhu, Carl Vondrick, Charless C. Fowlkes, Deva Ramanan
Learning Visual Biases from Human Imagination
Carl Vondrick, Hamed Pirsiavash, Aude Oliva, Antonio Torralba
HOGgles: Visualizing Object Detection Features
Carl Vondrick, Aditya Khosla, Tomasz Malisiewicz, Antonio Torralba
Do We Need More Training Data or Better Models for Object Detection?
Xiangxin Zhu, Carl Vondrick, Deva Ramanan, Charless C. Fowlkes
Large labeled datasets have enabled significant advancements in image understanding. However, there has not been as much progress in video understanding, possibly because labeled video data is much more expensive to annotate. We seek to develop better methods to annotate video efficiently.
Efficiently Scaling Up Crowdsourced Video Annotation
Carl Vondrick, Donald Patterson, Deva Ramanan
Video Annotation and Tracking with Active Learning
Carl Vondrick, Deva Ramanan
A Large-scale Benchmark Dataset for Event Recognition
Sangmin Oh, et al.
Efficiently Scaling Up Video Annotation with Crowdsourced Marketplaces
Carl Vondrick, Deva Ramanan, Donald Patterson
I'm normally not a praying man, but if you're up there, please save me, Superman. — Homer Simpson