7 papers · 1 filter
Modular Diffusion Models for Structured Visual Recognition
Siddhesh Khandelwal, Björn Ommer, Leonid Sigal
Traditional supervised methods for structured visual recognition tasks -- such as object detection, segmentation, and scene graph generation -- often produce deterministic, fixed o…
The Power of One: A Single Example is All it Takes for Segmentation in VLMs
Mir Rayat Imtiaz Hossain, Mennatullah Siam, Leonid Sigal +1
Large-scale vision-language models (VLMs), trained on extensive datasets of image-text pairs, exhibit strong multimodal understanding capabilities by implicitly learning associatio…
The ART of Composition: Attention-Regularized Training for Compositional Visual Grounding
Jiayun Luo, Mir Rayat Imtiaz Hossain, Pritam Sarkar +2
Vision-Language Models (VLMs) have achieved strong performance on implicit and explicit visual grounding and related tasks. However, such abilities are generally tested on simple,…
Black Swan: Abductive and Defeasible Video Reasoning in Unpredictable Events
Aditya Chinchure, Sahithya Ravi, Raymond Ng +3
The commonsense reasoning capabilities of vision-language models (VLMs), especially in abductive reasoning and defeasible reasoning, remain poorly understood. Most benchmarks focus…
Visual Prompting for Generalized Few-shot Segmentation: A Multi-scale Approach
Mir Rayat Imtiaz Hossain, Mennatullah Siam, Leonid Sigal +1
The emergence of attention-based transformer models has led to their extensive use in various tasks, due to their superior generalization and transfer properties. Recent research h…
TAM-VT: Transformation-Aware Multi-scale Video Transformer for Segmentation and Tracking
Raghav Goyal, Wan-Cyuan Fan, Mennatullah Siam +1
Video Object Segmentation (VOS) has emerged as an increasingly important problem with availability of larger datasets and more complex and realistic settings, which involve long vi…