1 citations · 2 across the 9 of their papers we have counts for
9 papers
TAKE 85: Testing Audiovisual filmmaKer's intEnt across 85 Hours of Film
Kaishuu Shinozaki-Conefrey, Olivier Pascaud, Robin Courant +3
Films communicate through deliberate creative choices, including lighting, color, composition, editing, dialogue, music, and sound. Humans naturally interpret these signals as dire…
Pathologist Attention-Aligned Report Generation for Prostate Histopathology
Ruoyu Xue, Suryakant Singh, Souradeep Chakraborty +12
The allocation of visual attention by pathologists during cancer diagnosis is a highly selective process that critically shapes the information extracted from whole-slide images (W…
LVLMs and Humans Ground Differently in Referential Communication
Peter Zeng, Weiling Li, Amie J. Paige +6
For generative AI agents to partner effectively with human users, the ability to accurately predict human intent is critical. But this ability to collaborate remains limited by a c…
Measuring and Predicting Where and When Pathologists Focus their Visual Attention while Grading Whole Slide Images of Cancer
Souradeep Chakraborty, Ruoyu Xue, Rajarsi Gupta +11
The ability to predict the attention of expert pathologists could lead to decision support systems for better pathology training. We developed methods to predict the spatio-tempora…
Decoding the visual attention of pathologists to reveal their level of expertise
Souradeep Chakraborty, Dana Perez, Paul Friedman +7
We present a method for classifying the expertise of a pathologist based on how they allocated their attention during a cancer reading. We engage this decoding task by developing a…
Self-supervised co-salient object detection via feature correspondence at multiple scales
Souradeep Chakraborty, Dimitris Samaras
Our paper introduces a novel two-stage self-supervised approach for detecting co-occurring salient objects (CoSOD) in image groups without requiring segmentation annotations. Unlik…
MORCIC: Model Order Reduction Techniques for Electromagnetic Models of Integrated Circuits
Dimitrios Garyfallou, Athanasios Stefanou, Christos Giamouzis +14
Model order reduction (MOR) is crucial for the design process of integrated circuits. Specifically, the vast amount of passive RLCk elements in electromagnetic models extracted fro…
Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics
Souradeep Chakraborty, Shujon Naha, Muhammet Bastan +2
In this paper, we address the detection of co-occurring salient objects (CoSOD) in an image group using frequency statistics in an unsupervised manner, which further enable us to d…
ChiMera: Learning with noisy labels by contrasting mixed-up augmentations
Zixuan Liu, Xin Zhang, Junjun He +5
Learning with noisy labels has been studied to address incorrect label annotations in real-world applications. In this paper, we present ChiMera, a two-stage learning-from-noisy-la…