Matthew Jin — accepted AI-conference papers

2024

3D Reconstruction of Objects in Hands without Real World 3D Supervision

Aditya Prakash*, Matthew Chang, Matthew Jin, Ruisen Tu, Saurabh Gupta

ECCV 2024poster

"Prior works for reconstructing hand-held objects from a single image train models on images paired with 3D shapes. Such data is challenging to gather in the real world at scale. Consequently, these approaches do not generalize well when presented with novel objects in in-the-wild settings. While 3D…

Cited by 2 Source ↗PDF ↗Scholar ↗

2022

MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction

Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy M Jackson, Mehdi Azabou +7

NeurIPS 2022accept

There are multiple scales of abstraction from which we can describe the same image, depending on whether we are focusing on fine-grained details or a more global attribute of the image. In brain mapping, learning to automatically parse images to build representations of both small-scale features (e.…

Cited by 5 Source ↗PDF ↗code ↗Scholar ↗