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20152026
most citedPosition, Padding and Predictions: A Deeper Look at Position Information in CNNs

42 citations · 161 across the 34 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CV2025

PuzzleCraft: Exploration-Aware Curriculum Learning for Puzzle-Based RLVR in VLMs

Ahmadreza Jeddi, Hakki Can Karaimer, Hue Nguyen +8

RL post-training with verifiable rewards (RLVR) has become a practical route to eliciting chain-of-thought reasoning in vision--language models (VLMs), but scaling it in the visual…

cs.CV2025

Generative Point Tracking with Flow Matching

Mattie Tesfaldet, Adam W. Harley, Konstantinos G. Derpanis +2

Tracking a point through a video can be a challenging task due to uncertainty arising from visual obfuscations, such as appearance changes and occlusions. Although current state-of…

cs.CV2025

Learn Your Scales: Towards Scale-Consistent Generative Novel View Synthesis

Fereshteh Forghani, Jason J. Yu, Tristan Aumentado-Armstrong +2

Conventional depth-free multi-view datasets are captured using a moving monocular camera without metric calibration. The scales of camera positions in this monocular setting are am…

cs.CV2025

Revisiting Image Fusion for Multi-Illuminant White-Balance Correction

David Serrano-Lozano, Aditya Arora, Luis Herranz +3

White balance (WB) correction in scenes with multiple illuminants remains a persistent challenge in computer vision. Recent methods explored fusion-based approaches, where a neural…

cs.CV2025

Geometry-Aware Diffusion Models for Multiview Scene Inpainting

Ahmad Salimi, Tristan Aumentado-Armstrong, Marcus A. Brubaker +1

In this paper, we focus on 3D scene inpainting, where parts of an input image set, captured from different viewpoints, are masked out. The main challenge lies in generating plausib…

cs.CV20251 cited

Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment

Harrish Thasarathan, Julian Forsyth, Thomas Fel +2

We present Universal Sparse Autoencoders (USAEs), a framework for uncovering and aligning interpretable concepts spanning multiple pretrained deep neural networks. Unlike existing…