103 citations · 233 across the 9 of their papers we have counts for
8 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…
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…
Frustratingly Simple but Effective Zero-shot Detection and Segmentation: Analysis and a Strong Baseline
Siddhesh Khandelwal, Anirudth Nambirajan, Behjat Siddiquie +2
Methods for object detection and segmentation often require abundant instance-level annotations for training, which are time-consuming and expensive to collect. To address this, th…
Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting
Benjamin Wilson, William Qi, Tanmay Agarwal +10
We introduce Argoverse 2 (AV2) - a collection of three datasets for perception and forecasting research in the self-driving domain. The annotated Sensor Dataset contains 1,000 sequ…
Iterative Scene Graph Generation
Siddhesh Khandelwal, Leonid Sigal
The task of scene graph generation entails identifying object entities and their corresponding interaction predicates in a given image (or video). Due to the combinatorially large…
Segmentation-grounded Scene Graph Generation
Siddhesh Khandelwal, Mohammed Suhail, Leonid Sigal
Scene graph generation has emerged as an important problem in computer vision. While scene graphs provide a grounded representation of objects, their locations and relations in an…
UniT: Unified Knowledge Transfer for Any-shot Object Detection and Segmentation
Siddhesh Khandelwal, Raghav Goyal, Leonid Sigal
Methods for object detection and segmentation rely on large scale instance-level annotations for training, which are difficult and time-consuming to collect. Efforts to alleviate t…
AttentionRNN: A Structured Spatial Attention Mechanism
Siddhesh Khandelwal, Leonid Sigal
Visual attention mechanisms have proven to be integrally important constituent components of many modern deep neural architectures. They provide an efficient and effective way to u…