1 citations · 2 across the 10 of their papers we have counts for
10 papers
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…
Do LLMs Benefit from User and Item Embeddings in Recommendation Tasks?
Mir Rayat Imtiaz Hossain, Leo Feng, Leonid Sigal +1
Large Language Models (LLMs) have emerged as promising recommendation systems, offering novel ways to model user preferences through generative approaches. However, many existing m…
ChartGaze: Enhancing Chart Understanding in LVLMs with Eye-Tracking Guided Attention Refinement
Ali Salamatian, Amirhossein Abaskohi, Wan-Cyuan Fan +3
Charts are a crucial visual medium for communicating and representing information. While Large Vision-Language Models (LVLMs) have made progress on chart question answering (CQA),…
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…
Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models
Jiayun Luo, Siddhesh Khandelwal, Leonid Sigal +1
From image-text pairs, large-scale vision-language models (VLMs) learn to implicitly associate image regions with words, which prove effective for tasks like visual question answer…
Framework-agnostic Semantically-aware Global Reasoning for Segmentation
Mir Rayat Imtiaz Hossain, Leonid Sigal, James J. Little
Recent advances in pixel-level tasks (e.g. segmentation) illustrate the benefit of of long-range interactions between aggregated region-based representations that can enhance local…