39 citations · 53 across the 7 of their papers we have counts for
7 papers
Semi-supervised Open-World Object Detection
Sahal Shaji Mullappilly, Abhishek Singh Gehlot, Rao Muhammad Anwer +2
Conventional open-world object detection (OWOD) problem setting first distinguishes known and unknown classes and then later incrementally learns the unknown objects when introduce…
3D Indoor Instance Segmentation in an Open-World
Mohamed El Amine Boudjoghra, Salwa K. Al Khatib, Jean Lahoud +4
Existing 3D instance segmentation methods typically assume that all semantic classes to be segmented would be available during training and only seen categories are segmented at in…
Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentation
Nian Liu, Kepan Nan, Wangbo Zhao +7
Few-Shot Video Object Segmentation (FSVOS) aims to segment objects in a query video with the same category defined by a few annotated support images. However, this task was seldom…
A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos
Chao Qin, Jiale Cao, Huazhu Fu +2
Detecting breast lesion in videos is crucial for computer-aided diagnosis. Existing video-based breast lesion detection approaches typically perform temporal feature aggregation of…
XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Models
Omkar Thawakar, Abdelrahman Shaker, Sahal Shaji Mullappilly +5
The latest breakthroughs in large vision-language models, such as Bard and GPT-4, have showcased extraordinary abilities in performing a wide range of tasks. Such models are traine…
Cross-modulated Few-shot Image Generation for Colorectal Tissue Classification
Amandeep Kumar, Ankan kumar Bhunia, Sanath Narayan +4
In this work, we propose a few-shot colorectal tissue image generation method for addressing the scarcity of histopathological training data for rare cancer tissues. Our few-shot g…
LEAPS: End-to-End One-Step Person Search With Learnable Proposals
Zhiqiang Dong, Jiale Cao, Rao Muhammad Anwer +3
We propose an end-to-end one-step person search approach with learnable proposals, named LEAPS. Given a set of sparse and learnable proposals, LEAPS employs a dynamic person search…