3.6k citations · 10.7k across the 127 of their papers we have counts for
145 papers
HorizonNet for visual terrain navigation
Bertil Grelsson, Andreas Robinson, Michael Felsberg +1
This paper investigates the problem of position estimation of unmanned surface vessels (USVs) operating in coastal areas or in the archipelago. We propose a position estimation met…
Gaussian-JEPA: Joint-Embedding Predictive Learning for 3D Gaussian Splats
Bin Ren, Qi Ma, Yue Li +7
3D Gaussian Splatting (3DGS) represents 3D content with anisotropic primitives that jointly encode geometry and appearance. Fixed-budget encoders consume sampled observations of Ga…
Improving Underwater Visual Tracking With a Large Scale Dataset and Image Enhancement
Basit Alawode, Fayaz Ali Dharejo, Mehnaz Ummar +6
This paper presents a new dataset and general tracker enhancement method for Underwater Visual Object Tracking (UVOT). Despite its significance, underwater tracking has remained un…
How Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges
Haotong Qin, Ge-Peng Ji, Salman Khan +3
Google's Bard has emerged as a formidable competitor to OpenAI's ChatGPT in the field of conversational AI. Notably, Bard has recently been updated to handle visual inputs alongsid…
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
Muhammad Uzair Khattak, Syed Talal Wasim, Muzammal Naseer +3
Prompt learning has emerged as an efficient alternative for fine-tuning foundational models, such as CLIP, for various downstream tasks. Conventionally trained using the task-speci…
Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment
Sheng Zhang, Muzammal Naseer, Guangyi Chen +4
Large-scale pre-trained Vision Language Models (VLMs) have proven effective for zero-shot classification. Despite the success, most traditional VLMs-based methods are restricted by…
Foundational Models Defining a New Era in Vision: A Survey and Outlook
Muhammad Awais, Muzammal Naseer, Salman Khan +5
Vision systems to see and reason about the compositional nature of visual scenes are fundamental to understanding our world. The complex relations between objects and their locatio…
Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation
Asif Hanif, Muzammal Naseer, Salman Khan +2
It is imperative to ensure the robustness of deep learning models in critical applications such as, healthcare. While recent advances in deep learning have improved the performance…
Video-FocalNets: Spatio-Temporal Focal Modulation for Video Action Recognition
Syed Talal Wasim, Muhammad Uzair Khattak, Muzammal Naseer +3
Recent video recognition models utilize Transformer models for long-range spatio-temporal context modeling. Video transformer designs are based on self-attention that can model glo…
PromptIR: Prompting for All-in-One Blind Image Restoration
Vaishnav Potlapalli, Syed Waqas Zamir, Salman Khan +1
Image restoration involves recovering a high-quality clean image from its degraded version. Deep learning-based methods have significantly improved image restoration performance, h…
DFormer: Diffusion-guided Transformer for Universal Image Segmentation
Hefeng Wang, Jiale Cao, Rao Muhammad Anwer +3
This paper introduces an approach, named DFormer, for universal image segmentation. The proposed DFormer views universal image segmentation task as a denoising process using a diff…
Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectors
Nicolae-Catalin Ristea, Florinel-Alin Croitoru, Radu Tudor Ionescu +3
We propose an efficient abnormal event detection model based on a lightweight masked auto-encoder (AE) applied at the video frame level. The novelty of the proposed model is threef…
Learnable Weight Initialization for Volumetric Medical Image Segmentation
Shahina Kunhimon, Abdelrahman Shaker, Muzammal Naseer +2
Hybrid volumetric medical image segmentation models, combining the advantages of local convolution and global attention, have recently received considerable attention. While mainly…
Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
Muhammad Maaz, Hanoona Rasheed, Salman Khan +1
Conversation agents fueled by Large Language Models (LLMs) are providing a new way to interact with visual data. While there have been initial attempts for image-based conversation…
Salient Mask-Guided Vision Transformer for Fine-Grained Classification
Dmitry Demidov, Muhammad Hamza Sharif, Aliakbar Abdurahimov +2
Fine-grained visual classification (FGVC) is a challenging computer vision problem, where the task is to automatically recognise objects from subordinate categories. One of its mai…
Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection
Long Li, Junwei Han, Ni Zhang +5
Most previous co-salient object detection works mainly focus on extracting co-salient cues via mining the consistency relations across images while ignoring explicit exploration of…
Modulate Your Spectrum in Self-Supervised Learning
Xi Weng, Yunhao Ni, Tengwei Song +5
Whitening loss offers a theoretical guarantee against feature collapse in self-supervised learning (SSL) with joint embedding architectures. Typically, it involves a hard whitening…
Gated Multi-Resolution Transfer Network for Burst Restoration and Enhancement
Nancy Mehta, Akshay Dudhane, Subrahmanyam Murala +3
Burst image processing is becoming increasingly popular in recent years. However, it is a challenging task since individual burst images undergo multiple degradations and often hav…
Vita-CLIP: Video and text adaptive CLIP via Multimodal Prompting
Syed Talal Wasim, Muzammal Naseer, Salman Khan +2
Adopting contrastive image-text pretrained models like CLIP towards video classification has gained attention due to its cost-effectiveness and competitive performance. However, re…
Boosting Adversarial Transferability using Dynamic Cues
Muzammal Naseer, Ahmad Mahmood, Salman Khan +1
The transferability of adversarial perturbations between image models has been extensively studied. In this case, an attack is generated from a known surrogate \eg, the ImageNet tr…
Video Instance Segmentation in an Open-World
Omkar Thawakar, Sanath Narayan, Hisham Cholakkal +5
Existing video instance segmentation (VIS) approaches generally follow a closed-world assumption, where only seen category instances are identified and spatio-temporally segmented…
Burstormer: Burst Image Restoration and Enhancement Transformer
Akshay Dudhane, Syed Waqas Zamir, Salman Khan +2
On a shutter press, modern handheld cameras capture multiple images in rapid succession and merge them to generate a single image. However, individual frames in a burst are misalig…
Generative Multiplane Neural Radiance for 3D-Aware Image Generation
Amandeep Kumar, Ankan Kumar Bhunia, Sanath Narayan +5
We present a method to efficiently generate 3D-aware high-resolution images that are view-consistent across multiple target views. The proposed multiplane neural radiance model, na…
3D-Aware Multi-Class Image-to-Image Translation with NeRFs
Senmao Li, Joost van de Weijer, Yaxing Wang +3
Recent advances in 3D-aware generative models (3D-aware GANs) combined with Neural Radiance Fields (NeRF) have achieved impressive results. However no prior works investigate 3D-aw…