1 citations · 3 across the 8 of their papers we have counts for
10 papers
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
SPEAR: A Simulator for Photorealistic Embodied AI Research
Mike Roberts, Renhan Wang, Rushikesh Zawar +10
Interactive simulators have become powerful tools for training embodied agents and generating synthetic visual data, but existing photorealistic simulators suffer from limited gene…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…
Towards Understanding Camera Motions in Any Video
Zhiqiu Lin, Siyuan Cen, Daniel Jiang +12
We introduce CameraBench, a large-scale dataset and benchmark designed to assess and improve camera motion understanding. CameraBench consists of ~3,000 diverse internet videos, an…
Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision Transformers
Andrew F. Luo, Jacob Yeung, Rushikesh Zawar +4
We introduce BrainSAIL, a method for linking neural selectivity with spatially distributed semantic visual concepts in natural scenes. BrainSAIL leverages recent advances in large-…
MaterialFusion: Enhancing Inverse Rendering with Material Diffusion Priors
Yehonathan Litman, Or Patashnik, Kangle Deng +4
Recent works in inverse rendering have shown promise in using multi-view images of an object to recover shape, albedo, and materials. However, the recovered components often fail t…
StableSemantics: A Synthetic Language-Vision Dataset of Semantic Representations in Naturalistic Images
Rushikesh Zawar, Shaurya Dewan, Andrew F. Luo +3
Understanding the semantics of visual scenes is a fundamental challenge in Computer Vision. A key aspect of this challenge is that objects sharing similar semantic meanings or func…
DiffusionPID: Interpreting Diffusion via Partial Information Decomposition
Rushikesh Zawar, Shaurya Dewan, Prakanshul Saxena +3
Text-to-image diffusion models have made significant progress in generating naturalistic images from textual inputs, and demonstrate the capacity to learn and represent complex vis…
Detecting Anomalies using Generative Adversarial Networks on Images
Rushikesh Zawar, Krupa Bhayani, Neelanjan Bhowmik +2
Automatic detection of anomalies such as weapons or threat objects in baggage security, or detecting impaired items in industrial production is an important computer vision task de…
Tuned Compositional Feature Replays for Efficient Stream Learning
Morgan B. Talbot, Rushikesh Zawar, Rohil Badkundri +2
Our brains extract durable, generalizable knowledge from transient experiences of the world. Artificial neural networks come nowhere close to this ability. When tasked with learnin…