27 citations · 53 across the 10 of their papers we have counts for
12 papers · 1 filter
From Global to Local: Rethinking CLIP Feature Aggregation for Person Re-Identification
Aotian Zheng, Winston Sun, Bahaa Alattar +2
CLIP-based person re-identification (ReID) methods aggregate spatial features into a single global \texttt{[CLS]} token optimized for image-text alignment rather than spatial selec…
SSP-GNN: Learning to Track via Bilevel Optimization
Griffin Golias, Masa Nakura-Fan, Vitaly Ablavsky
We propose a graph-based tracking formulation for multi-object tracking (MOT) where target detections contain kinematic information and re-identification features (attributes). Our…
The 7th AI City Challenge
Milind Naphade, Shuo Wang, David C. Anastasiu +17
The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems…
ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes
Dina Bashkirova, Mohamed Abdelfattah, Ziliang Zhu +7
Less than 35% of recyclable waste is being actually recycled in the US, which leads to increased soil and sea pollution and is one of the major concerns of environmental researcher…
The 5th AI City Challenge
Milind Naphade, Shuo Wang, David C. Anastasiu +11
The AI City Challenge was created with two goals in mind: (1) pushing the boundaries of research and development in intelligent video analysis for smarter cities use cases, and (2)…
CityFlow-NL: Tracking and Retrieval of Vehicles at City Scale by Natural Language Descriptions
Qi Feng, Vitaly Ablavsky, Stan Sclaroff
Natural Language (NL) descriptions can be one of the most convenient or the only way to interact with systems built to understand and detect city scale traffic patterns and vehicle…
Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System
Nataniel Ruiz, Hao Yu, Danielle A. Allessio +10
In this work, we propose a video-based transfer learning approach for predicting problem outcomes of students working with an intelligent tutoring system (ITS). By analyzing a stud…
DMCL: Distillation Multiple Choice Learning for Multimodal Action Recognition
Nuno C. Garcia, Sarah Adel Bargal, Vitaly Ablavsky +3
In this work, we address the problem of learning an ensemble of specialist networks using multimodal data, while considering the realistic and challenging scenario of possible miss…
Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese Trackers
Qi Feng, Vitaly Ablavsky, Qinxun Bai +1
We propose a novel Siamese Natural Language Tracker (SNLT), which brings the advancements in visual tracking to the tracking by natural language (NL) descriptions task. The propose…
Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes
Chenhongyi Yang, Vitaly Ablavsky, Kaihong Wang +2
While visual object detection with deep learning has received much attention in the past decade, cases when heavy intra-class occlusions occur have not been studied thoroughly. In…
Real-time Visual Object Tracking with Natural Language Description
Qi Feng, Vitaly Ablavsky, Qinxun Bai +2
In recent years, deep-learning-based visual object trackers have been studied thoroughly, but handling occlusions and/or rapid motion of the target remains challenging. In this wor…
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations
Hanxiao Wang, Venkatesh Saligrama, Stan Sclaroff +1
We consider the problem of fine-grained classification on an edge camera device that has limited power. The edge device must sparingly interact with the cloud to minimize communica…