113 citations · 360 across the 14 of their papers we have counts for
16 papers
Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond
Mohammadreza Armandpour, Ali Sadeghian, Huangjie Zheng +2
Although text-to-image diffusion models have made significant strides in generating images from text, they are sometimes more inclined to generate images like the data on which the…
3SD: Self-Supervised Saliency Detection With No Labels
Rajeev Yasarla, Renliang Weng, Wongun Choi +2
We present a conceptually simple self-supervised method for saliency detection. Our method generates and uses pseudo-ground truth labels for training. The generated pseudo-GT label…
JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset
Abhijeet Shenoi, Mihir Patel, JunYoung Gwak +5
Robots navigating autonomously need to perceive and track the motion of objects and other agents in its surroundings. This information enables planning and executing robust and saf…
Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks
Vineet Kosaraju, Amir Sadeghian, Roberto Martín-Martín +3
Predicting the future trajectories of multiple interacting agents in a scene has become an increasingly important problem for many different applications ranging from control of au…
Time-Varying Interaction Estimation Using Ensemble Methods
Brandon Oselio, Amir Sadeghian, Silvio Savarese +1
Directed information (DI) is a useful tool to explore time-directed interactions in multivariate data. However, as originally formulated DI is not well suited to interactions that…
Deep Local Trajectory Replanning and Control for Robot Navigation
Ashwini Pokle, Roberto Martín-Martín, Patrick Goebel +8
We present a navigation system that combines ideas from hierarchical planning and machine learning. The system uses a traditional global planner to compute optimal paths towards a…
Deep Visual MPC-Policy Learning for Navigation
Noriaki Hirose, Fei Xia, Roberto Martin-Martin +2
Humans can routinely follow a trajectory defined by a list of images/landmarks. However, traditional robot navigation methods require accurate mapping of the environment, localizat…
Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak +3
Intersection over Union (IoU) is the most popular evaluation metric used in the object detection benchmarks. However, there is a gap between optimizing the commonly used distance l…
VUNet: Dynamic Scene View Synthesis for Traversability Estimation using an RGB Camera
Noriaki Hirose, Amir Sadeghian, Fei Xia +2
We present VUNet, a novel view(VU) synthesis method for mobile robots in dynamic environments, and its application to the estimation of future traversability. Our method predicts f…
SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints
Amir Sadeghian, Vineet Kosaraju, Ali Sadeghian +3
This paper addresses the problem of path prediction for multiple interacting agents in a scene, which is a crucial step for many autonomous platforms such as self-driving cars and…
GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation
Noriaki Hirose, Amir Sadeghian, Marynel Vázquez +2
We present semi-supervised deep learning approaches for traversability estimation from fisheye images. Our method, GONet, and the proposed extensions leverage Generative Adversaria…
CAR-Net: Clairvoyant Attentive Recurrent Network
Amir Sadeghian, Ferdinand Legros, Maxime Voisin +3
We present an interpretable framework for path prediction that leverages dependencies between agents' behaviors and their spatial navigation environment. We exploit two sources of…
To Go or Not To Go? A Near Unsupervised Learning Approach For Robot Navigation
Noriaki Hirose, Amir Sadeghian, Patrick Goebel +1
It is important for robots to be able to decide whether they can go through a space or not, as they navigate through a dynamic environment. This capability can help them avoid inju…
Tracking The Untrackable: Learning To Track Multiple Cues with Long-Term Dependencies
Amir Sadeghian, Alexandre Alahi, Silvio Savarese
The majority of existing solutions to the Multi-Target Tracking (MTT) problem do not combine cues in a coherent end-to-end fashion over a long period of time. However, we present a…
Forecasting Social Navigation in Crowded Complex Scenes
Alexandre Robicquet, Alexandre Alahi, Amir Sadeghian +4
When humans navigate a crowed space such as a university campus or the sidewalks of a busy street, they follow common sense rules based on social etiquette. In this paper, we argue…
Feature Engineering for Knowledge Base Construction
Christopher Ré, Amir Abbas Sadeghian, Zifei Shan +4
Knowledge base construction (KBC) is the process of populating a knowledge base, i.e., a relational database together with inference rules, with information extracted from document…