289 citations · 655 across the 80 of their papers we have counts for
12 papers · 1 filter
Person Image Synthesis via Denoising Diffusion Model
Ankan Kumar Bhunia, Salman Khan, Hisham Cholakkal +4
The pose-guided person image generation task requires synthesizing photorealistic images of humans in arbitrary poses. The existing approaches use generative adversarial networks t…
An Investigation into Whitening Loss for Self-supervised Learning
Xi Weng, Lei Huang, Lei Zhao +3
A desirable objective in self-supervised learning (SSL) is to avoid feature collapse. Whitening loss guarantees collapse avoidance by minimizing the distance between embeddings of…
PS-ARM: An End-to-End Attention-aware Relation Mixer Network for Person Search
Mustansar Fiaz, Hisham Cholakkal, Sanath Narayan +2
Person search is a challenging problem with various real-world applications, that aims at joint person detection and re-identification of a query person from uncropped gallery imag…
CMR3D: Contextualized Multi-Stage Refinement for 3D Object Detection
Dhanalaxmi Gaddam, Jean Lahoud, Fahad Shahbaz Khan +2
Existing deep learning-based 3D object detectors typically rely on the appearance of individual objects and do not explicitly pay attention to the rich contextual information of th…
Transformers in Remote Sensing: A Survey
Abdulaziz Amer Aleissaee, Amandeep Kumar, Rao Muhammad Anwer +4
Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformers-based architectures,…
Multi-scale Feature Aggregation for Crowd Counting
Xiaoheng Jiang, Xinyi Wu, Hisham Cholakkal +5
Convolutional Neural Network (CNN) based crowd counting methods have achieved promising results in the past few years. However, the scale variation problem is still a huge challeng…
3D Vision with Transformers: A Survey
Jean Lahoud, Jiale Cao, Fahad Shahbaz Khan +4
The success of the transformer architecture in natural language processing has recently triggered attention in the computer vision field. The transformer has been used as a replace…
On the Robustness of 3D Object Detectors
Fatima Albreiki, Sultan Abughazal, Jean Lahoud +3
In recent years, significant progress has been achieved for 3D object detection on point clouds thanks to the advances in 3D data collection and deep learning techniques. Neverthel…
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications
Muhammad Maaz, Abdelrahman Shaker, Hisham Cholakkal +4
In the pursuit of achieving ever-increasing accuracy, large and complex neural networks are usually developed. Such models demand high computational resources and therefore cannot…
PSTR: End-to-End One-Step Person Search With Transformers
Jiale Cao, Yanwei Pang, Rao Muhammad Anwer +4
We propose a novel one-step transformer-based person search framework, PSTR, that jointly performs person detection and re-identification (re-id) in a single architecture. PSTR com…
Energy-based Latent Aligner for Incremental Learning
K J Joseph, Salman Khan, Fahad Shahbaz Khan +2
Deep learning models tend to forget their earlier knowledge while incrementally learning new tasks. This behavior emerges because the parameter updates optimized for the new tasks…
Video Instance Segmentation via Multi-scale Spatio-temporal Split Attention Transformer
Omkar Thawakar, Sanath Narayan, Jiale Cao +6
State-of-the-art transformer-based video instance segmentation (VIS) approaches typically utilize either single-scale spatio-temporal features or per-frame multi-scale features dur…