papers

Publications (10)

cs.CV2026

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence

Aman Tyagi, Hemanth Boinpally, Jonathan Chen +2

Modern black-box Image-to-Video (I2V) models offer powerful capabilities in automated content creation, yet their lack of fine-grained control and reliability presents significant…

cs.CV2019

Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction

Steven Hickson, Karthik Raveendran, Alireza Fathi +2

We propose 4 insights that help to significantly improve the performance of deep learning models that predict surface normals and semantic labels from a single RGB image. These ins…

cs.CV2018

Object category learning and retrieval with weak supervision

Steven Hickson, Anelia Angelova, Irfan Essa +1

We consider the problem of retrieving objects from image data and learning to classify them into meaningful semantic categories with minimal supervision. To that end, we propose a…

cs.CV2015

Predicting Daily Activities From Egocentric Images Using Deep Learning

Daniel Castro, Steven Hickson, Vinay Bettadapura +4

We present a method to analyze images taken from a passive egocentric wearable camera along with the contextual information, such as time and day of week, to learn and predict ever…

cs.CV2018

Efficient Hierarchical Graph-Based Segmentation of RGBD Videos

Steven Hickson, Stan Birchfield, Irfan Essa +1

We present an efficient and scalable algorithm for segmenting 3D RGBD point clouds by combining depth, color, and temporal information using a multistage, hierarchical graph-based…

cs.CV2017

An Energy Minimization Approach to 3D Non-Rigid Deformable Surface Estimation Using RGBD Data

Bryan Willimon, Steven Hickson, Ian Walker +1

We propose an algorithm that uses energy mini- mization to estimate the current configuration of a non-rigid object. Our approach utilizes an RGBD image to calculate corresponding…