1 citations · 1 across the 4 of their papers we have counts for
6 papers
ANCHOR: Audio-Visually Grounded Chain-of-Thought Reasoning Benchmark
Joel Julin, Souraja Kundu, Liza Dahiya +6
Multimodal large language models (MLLMs) perform well on audio-visual question answering, but correct answers do not necessarily imply that their stated reasoning is grounded in re…
PhySimCode: A Benchmark and Evaluation Method for Physics Video to Code Generation
Souraja Kundu, Aditya Gupta, Joel Julin +3
Multimodal large language models (MLLMs) are good at video understanding and code generation, but it remains unclear whether they can recover the physical laws underlying videos, a…
Rethinking the Role of Spatial Mixing
George Cazenavette, Joel Julin, Simon Lucey
Until quite recently, the backbone of nearly every state-of-the-art computer vision model has been the 2D convolution. At its core, a 2D convolution simultaneously mixes informatio…
Gaussian Splatting Lucas-Kanade
Liuyue Xie, Joel Julin, Koichiro Niinuma +1
Gaussian Splatting and its dynamic extensions are effective for reconstructing 3D scenes from 2D images when there is significant camera movement to facilitate motion parallax and…
CoGS: Controllable Gaussian Splatting
Heng Yu, Joel Julin, Zoltán Á. Milacski +2
Capturing and re-animating the 3D structure of articulated objects present significant barriers. On one hand, methods requiring extensively calibrated multi-view setups are prohibi…
DyLiN: Making Light Field Networks Dynamic
Heng Yu, Joel Julin, Zoltan A. Milacski +2
Light Field Networks, the re-formulations of radiance fields to oriented rays, are magnitudes faster than their coordinate network counterparts, and provide higher fidelity with re…