Trending Research
Relative Pose Estimation through Affine Corrections of Monocular Depth Priors
markyu98/madpose
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In this paper, we develop three solvers for relative pose estimation that explicitly account for independent affine (scale and shift) ambiguities, covering both calibrated and uncalibrated conditions.
Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs
Seamless operation of mobile robots in challenging environments requires low-latency local motion estimation (e. g., dynamic maneuvers) and accurate global localization (e. g., wayfinding).
UniK3D: Universal Camera Monocular 3D Estimation
Monocular 3D estimation is crucial for visual perception.
Ranked #2 on
Monocular Depth Estimation
on KITTI Eigen split
UI-TARS: Pioneering Automated GUI Interaction with Native Agents
This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e. g., keyboard and mouse operations).
TerraTorch: The Geospatial Foundation Models Toolkit
IBM/terratorch
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TerraTorch is a fine-tuning and benchmarking toolkit for Geospatial Foundation Models built on PyTorch Lightning and tailored for satellite, weather, and climate data.
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated reasoning, robust perception, and versatile action across diverse domains.
Ranked #1 on
Continual Learning
on AIDS
(using extra training data)
MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse
hiyouga/easyr1
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We present MetaSpatial, the first reinforcement learning (RL)-based framework designed to enhance 3D spatial reasoning in vision-language models (VLMs), enabling real-time 3D scene generation without the need for hard-coded optimizations.
Bitnet.cpp: Efficient Edge Inference for Ternary LLMs
microsoft/bitnet
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The advent of 1-bit large language models (LLMs), led by BitNet b1. 58, has spurred interest in ternary LLMs.
Olympus: A Universal Task Router for Computer Vision Tasks
We introduce Olympus, a new approach that transforms Multimodal Large Language Models (MLLMs) into a unified framework capable of handling a wide array of computer vision tasks.
SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
To address this, we co-design an inference engine Nunchaku that fuses the kernels of the low-rank branch into those of the low-bit branch to cut off redundant memory access.
