36 citations · 194 across the 34 of their papers we have counts for
13 papers · 1 filter
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
Micah Goldblum, Hossein Souri, Renkun Ni +10
Neural network based computer vision systems are typically built on a backbone, a pretrained or randomly initialized feature extractor. Several years ago, the default option was an…
Whole-body Detection, Recognition and Identification at Altitude and Range
Siyuan Huang, Ram Prabhakar Kathirvel, Chun Pong Lau +1
In this paper, we address the challenging task of whole-body biometric detection, recognition, and identification at distances of up to 500m and large pitch angles of up to 50 degr…
Learning to Prompt Your Domain for Vision-Language Models
Guoyizhe Wei, Feng Wang, Anshul Shah +1
Prompt learning has recently become a very efficient transfer learning paradigm for Contrastive Language Image Pretraining (CLIP) models. Compared with fine-tuning the entire encod…
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Mahyar Fazlyab, Taha Entesari, Aniket Roy +1
To improve the robustness of deep classifiers against adversarial perturbations, many approaches have been proposed, such as designing new architectures with better robustness prop…
ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning
Qiao Gu, Alihusein Kuwajerwala, Sacha Morin +13
For robots to perform a wide variety of tasks, they require a 3D representation of the world that is semantically rich, yet compact and efficient for task-driven perception and pla…
EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the Backbone
Shraman Pramanick, Yale Song, Sayan Nag +5
Video-language pre-training (VLP) has become increasingly important due to its ability to generalize to various vision and language tasks. However, existing egocentric VLP framewor…
SMC-UDA: Structure-Modal Constraint for Unsupervised Cross-Domain Renal Segmentation
Zhusi Zhong, Jie Li, Lulu Bi +6
Medical image segmentation based on deep learning often fails when deployed on images from a different domain. The domain adaptation methods aim to solve domain-shift challenges, b…
Attribute-Guided Encryption with Facial Texture Masking
Chun Pong Lau, Jiang Liu, Rama Chellappa
The increasingly pervasive facial recognition (FR) systems raise serious concerns about personal privacy, especially for billions of users who have publicly shared their photos on…
DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection
Jiang Liu, Chun Pong Lau, Zhongliang Guo +3
The increasingly pervasive facial recognition (FR) systems raise serious concerns about personal privacy, especially for billions of users who have publicly shared their photos on…
The 7th AI City Challenge
Milind Naphade, Shuo Wang, David C. Anastasiu +17
The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems…
HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised Learning of Actions
Anshul Shah, Aniket Roy, Ketul Shah +4
Supervised learning of skeleton sequence encoders for action recognition has received significant attention in recent times. However, learning such encoders without labels continue…
Synthetic-to-Real Domain Adaptation for Action Recognition: A Dataset and Baseline Performances
Arun V. Reddy, Ketul Shah, William Paul +6
Human action recognition is a challenging problem, particularly when there is high variability in factors such as subject appearance, backgrounds and viewpoint. While deep neural n…
STEPs: Self-Supervised Key Step Extraction and Localization from Unlabeled Procedural Videos
Anshul Shah, Benjamin Lundell, Harpreet Sawhney +1
We address the problem of extracting key steps from unlabeled procedural videos, motivated by the potential of Augmented Reality (AR) headsets to revolutionize job training and per…