1 code implementation • ICML 2018 • Si Liu, Risheek Garrepalli, Thomas G. Dietterich, Alan Fern, Dan Hendrycks
Further, while there are algorithms for open category detection, there are few empirical results that directly report alien detection rates.
no code implementations • CVPR 2022 • Shubhankar Borse, Hyojin Park, Hong Cai, Debasmit Das, Risheek Garrepalli, Fatih Porikli
A Panoptic Relational Attention (PRA) module is then applied to the encodings and the global feature map from the backbone.
no code implementations • 22 Sep 2022 • Risheek Garrepalli
The second is to introduce Oracle representation learning, which produces a representation that is guaranteed to be sufficient for accurate anomaly detection.
no code implementations • 24 Feb 2023 • Debasmit Das, Shubhankar Borse, Hyojin Park, Kambiz Azarian, Hong Cai, Risheek Garrepalli, Fatih Porikli
Test-time adaptive (TTA) semantic segmentation adapts a source pre-trained image semantic segmentation model to unlabeled batches of target domain test images, different from real-world, where samples arrive one-by-one in an online fashion.
no code implementations • CVPR 2023 • Shubhankar Borse, Debasmit Das, Hyojin Park, Hong Cai, Risheek Garrepalli, Fatih Porikli
Next, we use a conditional regenerator, which takes the redacted image and the dense predictions as inputs, and reconstructs the original image by filling in the missing structural information.
no code implementations • CVPR 2023 • Jisoo Jeong, Hong Cai, Risheek Garrepalli, Fatih Porikli
We propose a novel data augmentation approach, DistractFlow, for training optical flow estimation models by introducing realistic distractions to the input frames.
no code implementations • 9 Jun 2023 • Risheek Garrepalli, Jisoo Jeong, Rajeswaran C Ravindran, Jamie Menjay Lin, Fatih Porikli
Also, we present a novel dynamic coarse-to-fine cost volume processing during various stages of refinement to avoid multiple levels of cost volumes.
no code implementations • IEEE/CVF International Conference on Computer Vision (ICCV) 2023 • Rajeev Yasarla, Hong Cai, Jisoo Jeong, Yunxiao Shi, Risheek Garrepalli, Fatih Porikli
We propose MAMo, a novel memory and attention frame-work for monocular video depth estimation.
Ranked #11 on Monocular Depth Estimation on KITTI Eigen split
1 code implementation • 13 Dec 2023 • Amirhossein Habibian, Amir Ghodrati, Noor Fathima, Guillaume Sautiere, Risheek Garrepalli, Fatih Porikli, Jens Petersen
This work aims to improve the efficiency of text-to-image diffusion models.
no code implementations • 19 Mar 2024 • Rajeev Yasarla, Manish Kumar Singh, Hong Cai, Yunxiao Shi, Jisoo Jeong, Yinhao Zhu, Shizhong Han, Risheek Garrepalli, Fatih Porikli
In this paper, we propose a novel video depth estimation approach, FutureDepth, which enables the model to implicitly leverage multi-frame and motion cues to improve depth estimation by making it learn to predict the future at training.
Ranked #1 on Monocular Depth Estimation on KITTI Eigen split
no code implementations • 26 Mar 2024 • Jisoo Jeong, Hong Cai, Risheek Garrepalli, Jamie Menjay Lin, Munawar Hayat, Fatih Porikli
We propose OCAI, a method that supports robust frame interpolation by generating intermediate video frames alongside optical flows in between.
no code implementations • 11 Apr 2024 • Jamie Menjay Lin, Jisoo Jeong, Hong Cai, Risheek Garrepalli, Kai Wang, Fatih Porikli
Optical flow estimation is crucial to a variety of vision tasks.