1 citations · 1 across the 2 of their papers we have counts for
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Anchored, Not Graded: Vision-Language Models Fail at Slant-from-Texture Perception
Qian Zhang, Michal Golovanevsky, Fulvio Domini +1
Human perception of surface slant from texture exhibits systematic, graded biases that emerge reliably in psychophysical experiments. Prior work showed that unsupervised CNNs repro…
TreeDGS: Aerial Gaussian Splatting for Distant DBH Measurement
Belal Shaheen, Minh-Hieu Nguyen, Bach-Thuan Bui +6
Aerial remote sensing efficiently surveys large areas, but accurate direct object-level measurement remains difficult in complex natural scenes. Advancements in 3D computer vision,…
Disentangling 3D from Large Vision-Language Models for Controlled Portrait Generation
Nick Yiwen Huang, Akin Caliskan, Berkay Kicanaoglu +2
We consider the problem of disentangling 3D from large vision-language models, which we show on generative 3D portraits. This allows free-form text control of appearance attributes…
Monocular Dynamic Gaussian Splatting: Fast, Brittle, and Scene Complexity Rules
Yiqing Liang, Mikhail Okunev, Mikaela Angelina Uy +4
Gaussian splatting methods are emerging as a popular approach for converting multi-view image data into scene representations that allow view synthesis. In particular, there is int…
MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning
Yiqing Liang, Jielin Qiu, Wenhao Ding +7
Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as a powerful paradigm for post-training large language models (LLMs), achieving state-of-the-art perform…
Zero-Shot Monocular Scene Flow Estimation in the Wild
Yiqing Liang, Abhishek Badki, Hang Su +2
Large models have shown generalization across datasets for many low-level vision tasks, like depth estimation, but no such general models exist for scene flow. Even though scene fl…