Perception Programs Cvpr 2026

Media Summary: Video for the paper "Don't Show Pixels, Show Cues: Unlocking Visual Tool Reasoning in Language Models via Rameen Abdal, James Burgess, Sergey Tulyakov, Kuan-Chieh Wang Snap Research , Stanford University ... Title: Scene-Centric Unsupervised Video Panoptic Segmentation Authors: Christoph Reich*, Oliver Hahn*, Nikita Araslanov, ...

Perception Programs Cvpr 2026 - Detailed Analysis & Overview

Video for the paper "Don't Show Pixels, Show Cues: Unlocking Visual Tool Reasoning in Language Models via Rameen Abdal, James Burgess, Sergey Tulyakov, Kuan-Chieh Wang Snap Research , Stanford University ... Title: Scene-Centric Unsupervised Video Panoptic Segmentation Authors: Christoph Reich*, Oliver Hahn*, Nikita Araslanov, ... [CVPR 2026] iSHIFT: Lightweight Slow-Fast GUI Agent with Adaptive Perception [CVPR 2026] GenMatter: Perceiving Physical Objects with Generative Matter Models Omni-Attribute encodes a high-fidelity, attribute-specific image representation, that enables coherent synthesis of the ...

NeuroFlow: Toward Unified Visual Encoding and Decoding from Neural Activity. [CVPR 2026] Aligning What Vision-Language Models See and Perceive with Adaptive Information Flow Disentangle-then-Align: Non-Iterative Hybrid Multimodal Image Registration via Cross-Scale Feature Disentanglement. We present a systematic empirical study of Test-Time Training designs for vision, distilling six practical insights for building ... [CVPR 2026] PR-MaGIC: Prompt Refinement via Mask Decoder Gradient Flow for In-Context Segmentation [CVPR 2026] ConsID-Gen: View-Consistent and Identity-Preserving Image-to-Video Generation

MERL researcher Pedro Miraldo presents the paper “Revisiting Monocular SLAM with Spatio-Temporal Scene Modeling” at the ...