Trending Research
ImageNet Classification with Deep Convolutional Neural Networks
We trained a large, deep convolutional neural network to classify the 1. 3 million high-resolution images in the LSVRC-2010 ImageNet training set into the 1000 different classes.
Ranked #4 on
Graph Classification
on HIV-fMRI-77
InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity
Achieving flexible and high-fidelity identity-preserved image generation remains formidable, particularly with advanced Diffusion Transformers (DiTs) like FLUX.
Long-Context Autoregressive Video Modeling with Next-Frame Prediction
showlab/FAR
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Existing RoPE lacks effective temporal decay for remote context and fails to extrapolate well to long video sequences.
Ranked #2 on
Video Generation
on UCF-101
LHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds
aigc3d/LHM
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Animatable 3D human reconstruction from a single image is a challenging problem due to the ambiguity in decoupling geometry, appearance, and deformation.
UniK3D: Universal Camera Monocular 3D Estimation
Monocular 3D estimation is crucial for visual perception.
Ranked #2 on
Monocular Depth Estimation
on KITTI Eigen split
VGGT: Visual Geometry Grounded Transformer
We present VGGT, a feed-forward neural network that directly infers all key 3D attributes of a scene, including camera parameters, point maps, depth maps, and 3D point tracks, from one, a few, or hundreds of its views.
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).
KBLaM: Knowledge Base augmented Language Model
microsoft/KBLaM
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In this paper, we propose Knowledge Base augmented Language Model (KBLaM), a new method for augmenting Large Language Models (LLMs) with external knowledge.
Fin-R1: A Large Language Model for Financial Reasoning through Reinforcement Learning
Reasoning large language models are rapidly evolving across various domains.
Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens
Recent advancements in large language models (LLMs) have driven significant progress in zero-shot text-to-speech (TTS) synthesis.
