10 papers · 1 filter
Position: Unlabeled IS NOT Equal to No Human Supervision in Visual Learning
Dong Lao
This position paper argues that the absence of labels does not imply the absence of human supervision in visual learning, and urges the research community to identify sources of su…
Triangular Consistency as a Universal Constraint for Learning Optical Flow
Yi Xiao, Carlos Rodriguez Coronel, Jing Zhan +3
We propose triangular consistency as a first-principled constraint for optical flow, which is agnostic to network architecture, supervision type, and dataset, and applies to both i…
Naïve PAINE: Lightweight Text-to-Image Generation Improvement with Prompt Evaluation
Joong Ho Kim, Nicholas Thai, Souhardya Saha Dip +2
Text-to-Image (T2I) generation is primarily driven by Diffusion Models (DM) which rely on random Gaussian noise. Thus, like playing the slots at a casino, a DM will produce differe…
Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles
Dong Lao, Yuxiang Zhang, Haniyeh Ehsani Oskouie +3
We propose a test-time defense mechanism against adversarial attacks: imperceptible image perturbations that significantly alter the predictions of a model. Unlike existing methods…
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions
Ziyao Zeng, Yangchao Wu, Hyoungseob Park +6
We propose a method for metric-scale monocular depth estimation. Inferring depth from a single image is an ill-posed problem due to the loss of scale from perspective projection du…
Diffeomorphic Template Registration for Atmospheric Turbulence Mitigation
Dong Lao, Congli Wang, Alex Wong +1
We describe a method for recovering the irradiance underlying a collection of images corrupted by atmospheric turbulence. Since supervised data is often technically impossible to o…