4.4k citations · 9.7k across the 80 of their papers we have counts for
22 papers · 2 filters
OW-DETR: Open-world Detection Transformer
Akshita Gupta, Sanath Narayan, K J Joseph +3
Open-world object detection (OWOD) is a challenging computer vision problem, where the task is to detect a known set of object categories while simultaneously identifying unknown o…
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection
Nicolae-Catalin Ristea, Neelu Madan, Radu Tudor Ionescu +4
Anomaly detection is commonly pursued as a one-class classification problem, where models can only learn from normal training samples, while being evaluated on both normal and abno…
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection
Andra Acsintoae, Andrei Florescu, Mariana-Iuliana Georgescu +5
Detecting abnormal events in video is commonly framed as a one-class classification task, where training videos contain only normal events, while test videos encompass both normal…
"Knights": First Place Submission for VIPriors21 Action Recognition Challenge at ICCV 2021
Ishan Dave, Naman Biyani, Brandon Clark +3
This technical report presents our approach "Knights" to solve the action recognition task on a small subset of Kinetics-400 i.e. Kinetics400ViPriors without using any extra-data.…
Discriminative Region-based Multi-Label Zero-Shot Learning
Sanath Narayan, Akshita Gupta, Salman Khan +3
Multi-label zero-shot learning (ZSL) is a more realistic counter-part of standard single-label ZSL since several objects can co-exist in a natural image. However, the occurrence of…
Video Generation from Text Employing Latent Path Construction for Temporal Modeling
Amir Mazaheri, Mubarak Shah
Video generation is one of the most challenging tasks in Machine Learning and Computer Vision fields of study. In this paper, we tackle the text to video generation problem, which…
TinyAction Challenge: Recognizing Real-world Low-resolution Activities in Videos
Praveen Tirupattur, Aayush J Rana, Tushar Sangam +3
This paper summarizes the TinyAction challenge which was organized in ActivityNet workshop at CVPR 2021. This challenge focuses on recognizing real-world low-resolution activities…
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Dawei Du, Longyin Wen, Pengfei Zhu +52
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.…
Controlled Caption Generation for Images Through Adversarial Attacks
Nayyer Aafaq, Naveed Akhtar, Wei Liu +2
Deep learning is found to be vulnerable to adversarial examples. However, its adversarial susceptibility in image caption generation is under-explored. We study adversarial example…
Florida Wildlife Camera Trap Dataset
Crystal Gagne, Jyoti Kini, Daniel Smith +1
Trail camera imagery has increasingly gained popularity amongst biologists for conservation and ecological research. Minimal human interference required to operate camera traps all…
Novel View Video Prediction Using a Dual Representation
Sarah Shiraz, Krishna Regmi, Shruti Vyas +2
We address the problem of novel view video prediction; given a set of input video clips from a single/multiple views, our network is able to predict the video from a novel view. Th…
PC-DAN: Point Cloud based Deep Affinity Network for 3D Multi-Object Tracking (Accepted as an extended abstract in JRDB-ACT Workshop at CVPR21)
Aakash Kumar, Jyoti Kini, Mubarak Shah +1
In recent times, the scope of LIDAR (Light Detection and Ranging) sensor-based technology has spread across numerous fields. It is popularly used to map terrain and navigation info…
PLM: Partial Label Masking for Imbalanced Multi-label Classification
Kevin Duarte, Yogesh S. Rawat, Mubarak Shah
Neural networks trained on real-world datasets with long-tailed label distributions are biased towards frequent classes and perform poorly on infrequent classes. The imbalance in t…
Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules
Aisha Urooj Khan, Hilde Kuehne, Kevin Duarte +3
The problem of grounding VQA tasks has seen an increased attention in the research community recently, with most attempts usually focusing on solving this task by using pretrained…
MutualNet: Adaptive ConvNet via Mutual Learning from Different Model Configurations
Taojiannan Yang, Sijie Zhu, Matias Mendieta +6
Most existing deep neural networks are static, which means they can only do inference at a fixed complexity. But the resource budget can vary substantially across different devices…
Unsupervised Discriminative Embedding for Sub-Action Learning in Complex Activities
Sirnam Swetha, Hilde Kuehne, Yogesh S Rawat +1
Action recognition and detection in the context of long untrimmed video sequences has seen an increased attention from the research community. However, annotation of complex activi…
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan +1
In many real-world problems, collecting a large number of labeled samples is infeasible. Few-shot learning (FSL) is the dominant approach to address this issue, where the objective…
Dogfight: Detecting Drones from Drones Videos
Muhammad Waseem Ashraf, Waqas Sultani, Mubarak Shah
As airborne vehicles are becoming more autonomous and ubiquitous, it has become vital to develop the capability to detect the objects in their surroundings. This paper attempts to…
Handwriting Transformers
Ankan Kumar Bhunia, Salman Khan, Hisham Cholakkal +3
We propose a novel transformer-based styled handwritten text image generation approach, HWT, that strives to learn both style-content entanglement as well as global and local writi…
LSDAT: Low-Rank and Sparse Decomposition for Decision-based Adversarial Attack
Ashkan Esmaeili, Marzieh Edraki, Nazanin Rahnavard +2
We propose LSDAT, an image-agnostic decision-based black-box attack that exploits low-rank and sparse decomposition (LSD) to dramatically reduce the number of queries and achieve s…
Modeling Multi-Label Action Dependencies for Temporal Action Localization
Praveen Tirupattur, Kevin Duarte, Yogesh Rawat +1
Real-world videos contain many complex actions with inherent relationships between action classes. In this work, we propose an attention-based architecture that models these action…
Transformers in Vision: A Survey
Salman Khan, Muzammal Naseer, Munawar Hayat +3
Astounding results from Transformer models on natural language tasks have intrigued the vision community to study their application to computer vision problems. Among their salient…