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20152023
most citedTraining Neural Networks Without Gradients: A Scalable ADMM Approach

140 citations · 382 across the 16 of their papers we have counts for

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20 papers · 1 filter

cs.CV2023

LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation

Koutilya Pnvr, Bharat Singh, Pallabi Ghosh +2

Large-scale pre-training tasks like image classification, captioning, or self-supervised techniques do not incentivize learning the semantic boundaries of objects. However, recent…

cs.CV2021

Scale Normalized Image Pyramids with AutoFocus for Object Detection

Bharat Singh, Mahyar Najibi, Abhishek Sharma +1

We present an efficient foveal framework to perform object detection. A scale normalized image pyramid (SNIP) is generated that, like human vision, only attends to objects within a…

cs.CV2020★ 3 cited

ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors

Rohun Tripathi, Vasu Singla, Mahyar Najibi +3

The widely adopted sequential variant of Non Maximum Suppression (or Greedy-NMS) is a crucial module for object-detection pipelines. Unfortunately, for the region proposal stage of…

cs.CV2019★ 1 cited

Recognizing Instagram Filtered Images with Feature De-stylization

Zhe Wu, Zuxuan Wu, Bharat Singh +1

Deep neural networks have been shown to suffer from poor generalization when small perturbations are added (like Gaussian noise), yet little work has been done to evaluate their ro…

cs.CV2019★ 1 cited

Automatic Long-Term Deception Detection in Group Interaction Videos

Chongyang Bai, Maksim Bolonkin, Judee Burgoon +5

Most work on automated deception detection (ADD) in video has two restrictions: (i) it focuses on a video of one person, and (ii) it focuses on a single act of deception in a one o…

cs.CV2019★ 33 cited

An Analysis of Pre-Training on Object Detection

Hengduo Li, Bharat Singh, Mahyar Najibi +2

We provide a detailed analysis of convolutional neural networks which are pre-trained on the task of object detection. To this end, we train detectors on large datasets like OpenIm…