4.3k citations · 28.6k across the 204 of their papers we have counts for
15 papers · 2 filters
Constrained Structured Regression with Convolutional Neural Networks
Deepak Pathak, Philipp Krähenbühl, Stella X. Yu +1
Convolutional Neural Networks (CNNs) have recently emerged as the dominant model in computer vision. If provided with enough training data, they predict almost any visual quantity.…
Fine-grained pose prediction, normalization, and recognition
Ning Zhang, Evan Shelhamer, Yang Gao +1
Pose variation and subtle differences in appearance are key challenges to fine-grained classification. While deep networks have markedly improved general recognition, many approach…
Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets
Takuya Narihira, Damian Borth, Stella X. Yu +2
We consider the visual sentiment task of mapping an image to an adjective noun pair (ANP) such as "cute baby". To capture the two-factor structure of our ANP semantics as well as t…
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints
Eric Tzeng, Coline Devin, Judy Hoffman +5
Real-world robotics problems often occur in domains that differ significantly from the robot's prior training environment. For many robotic control tasks, real world experience is…
Auxiliary Image Regularization for Deep CNNs with Noisy Labels
Samaneh Azadi, Jiashi Feng, Stefanie Jegelka +1
Precisely-labeled data sets with sufficient amount of samples are very important for training deep convolutional neural networks (CNNs). However, many of the available real-world d…
Data-dependent Initializations of Convolutional Neural Networks
Philipp Krähenbühl, Carl Doersch, Jeff Donahue +1
Convolutional Neural Networks spread through computer vision like a wildfire, impacting almost all visual tasks imaginable. Despite this, few researchers dare to train their models…