1.6k citations · 3.1k across the 115 of their papers we have counts for
4 papers · 2 filters
Deep Multi-Modal Image Correspondence Learning
Chen Liu, Jiajun Wu, Pushmeet Kohli +1
Inference of correspondences between images from different modalities is an extremely important perceptual ability that enables humans to understand and recognize cross-modal conce…
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue +2
We study the problem of 3D object generation. We propose a novel framework, namely 3D Generative Adversarial Network (3D-GAN), which generates 3D objects from a probabilistic space…
Ambient Sound Provides Supervision for Visual Learning
Andrew Owens, Jiajun Wu, Josh H. McDermott +2
The sound of crashing waves, the roar of fast-moving cars -- sound conveys important information about the objects in our surroundings. In this work, we show that ambient sounds ca…
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
Tianfan Xue, Jiajun Wu, Katherine L. Bouman +1
We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods, which have tackled this problem in a determinis…