Search Results for author: Sagar Vaze

Found 9 papers, 4 papers with code

SPTNet: An Efficient Alternative Framework for Generalized Category Discovery with Spatial Prompt Tuning

no code implementations20 Mar 2024 Hongjun Wang, Sagar Vaze, Kai Han

We thoroughly evaluate our SPTNet on standard benchmarks and demonstrate that our method outperforms existing GCD methods.

GeneCIS: A Benchmark for General Conditional Image Similarity

no code implementations CVPR 2023 Sagar Vaze, Nicolas Carion, Ishan Misra

In this paper, we propose the GeneCIS ('genesis') benchmark, which measures models' ability to adapt to a range of similarity conditions.

Image Retrieval Representation Learning

What's in a Name? Beyond Class Indices for Image Recognition

no code implementations5 Apr 2023 Kai Han, Yandong Li, Sagar Vaze, Jie Li, Xuhui Jia

In this paper, we reconsider the recognition problem and task a vision-language model to assign class names to images given only a large and essentially unconstrained vocabulary of categories as prior information.

Language Modelling Object Recognition

Zero-Shot Category-Level Object Pose Estimation

1 code implementation7 Apr 2022 Walter Goodwin, Sagar Vaze, Ioannis Havoutis, Ingmar Posner

Object pose estimation is an important component of most vision pipelines for embodied agents, as well as in 3D vision more generally.

Object Pose Estimation

Semantically Grounded Object Matching for Robust Robotic Scene Rearrangement

1 code implementation15 Nov 2021 Walter Goodwin, Sagar Vaze, Ioannis Havoutis, Ingmar Posner

Object rearrangement has recently emerged as a key competency in robot manipulation, with practical solutions generally involving object detection, recognition, grasping and high-level planning.

Language Modelling Object +3

Open-Set Recognition: a Good Closed-Set Classifier is All You Need?

2 code implementations ICLR 2022 Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman

In this paper, we first demonstrate that the ability of a classifier to make the 'none-of-above' decision is highly correlated with its accuracy on the closed-set classes.

Open Set Learning Out-of-Distribution Detection

SMArtCast: Predicting soil moisture interpolations into the future using Earth observation data in a deep learning framework

no code implementations16 Mar 2020 Conrad James Foley, Sagar Vaze, Mohamed El Amine Seddiq, Alexey Unagaev, Natalia Efremova

Soil moisture is critical component of crop health and monitoring it can enable further actions for increasing yield or preventing catastrophic die off.

Cannot find the paper you are looking for? You can Submit a new open access paper.