68 citations · 184 across the 10 of their papers we have counts for
10 papers
Goal-driven text descriptions for images
Ruotian Luo
A big part of achieving Artificial General Intelligence(AGI) is to build a machine that can see and listen like humans. Much work has focused on designing models for image classifi…
Controlling Length in Image Captioning
Ruotian Luo, Greg Shakhnarovich
We develop and evaluate captioning models that allow control of caption length. Our models can leverage this control to generate captions of different style and descriptiveness.
Detection and Description of Change in Visual Streams
Davis Gilton, Ruotian Luo, Rebecca Willett +1
This paper presents a framework for the analysis of changes in visual streams: ordered sequences of images, possibly separated by significant time gaps. We propose a new approach t…
Pixel Consensus Voting for Panoptic Segmentation
Haochen Wang, Ruotian Luo, Michael Maire +1
The core of our approach, Pixel Consensus Voting, is a framework for instance segmentation based on the Generalized Hough transform. Pixels cast discretized, probabilistic votes fo…
A Better Variant of Self-Critical Sequence Training
Ruotian Luo
In this work, we present a simple yet better variant of Self-Critical Sequence Training. We make a simple change in the choice of baseline function in REINFORCE algorithm. The new…
Analysis of diversity-accuracy tradeoff in image captioning
Ruotian Luo, Gregory Shakhnarovich
We investigate the effect of different model architectures, training objectives, hyperparameter settings and decoding procedures on the diversity of automatically generated image c…
DIODE: A Dense Indoor and Outdoor DEpth Dataset
Igor Vasiljevic, Nick Kolkin, Shanyi Zhang +8
We introduce DIODE, a dataset that contains thousands of diverse high resolution color images with accurate, dense, long-range depth measurements. DIODE (Dense Indoor/Outdoor DEpth…
Context-Aware Zero-Shot Recognition
Ruotian Luo, Ning Zhang, Bohyung Han +1
We present a novel problem setting in zero-shot learning, zero-shot object recognition and detection in the context. Contrary to the traditional zero-shot learning methods, which s…
Discriminability objective for training descriptive captions
Ruotian Luo, Brian Price, Scott Cohen +1
One property that remains lacking in image captions generated by contemporary methods is discriminability: being able to tell two images apart given the caption for one of them. We…
Comprehension-guided referring expressions
Ruotian Luo, Gregory Shakhnarovich
We consider generation and comprehension of natural language referring expression for objects in an image. Unlike generic "image captioning" which lacks natural standard evaluation…