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20162025
most citedTraining Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution

11 citations · 11 across the 14 of their papers we have counts for

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9 papers · 1 filter

cs.CV2025

Latent Visual Reasoning

Bangzheng Li, Ximeng Sun, Jiang Liu +7

Multimodal Large Language Models (MLLMs) have achieved notable gains in various tasks by incorporating Chain-of-Thought (CoT) reasoning in language spaces. Recent work extends this…

cs.CV2025

SpecVLM: Fast Speculative Decoding in Vision-Language Models

Haiduo Huang, Fuwei Yang, Zhenhua Liu +4

Speculative decoding is a powerful way to accelerate autoregressive large language models (LLMs), but directly porting it to vision-language models (VLMs) faces unique systems cons…

cs.CV2025

Instella-T2I: Pushing the Limits of 1D Discrete Latent Space Image Generation

Ze Wang, Hao Chen, Benran Hu +7

Image tokenization plays a critical role in reducing the computational demands of modeling high-resolution images, significantly improving the efficiency of image and multimodal un…

cs.CV2025

DL-QAT: Weight-Decomposed Low-Rank Quantization-Aware Training for Large Language Models

Wenjin Ke, Zhe Li, Dong Li +2

Improving the efficiency of inference in Large Language Models (LLMs) is a critical area of research. Post-training Quantization (PTQ) is a popular technique, but it often faces ch…

cs.CV2025

MonoGS++: Fast and Accurate Monocular RGB Gaussian SLAM

Renwu Li, Wenjing Ke, Dong Li +2

We present MonoGS++, a novel fast and accurate Simultaneous Localization and Mapping (SLAM) method that leverages 3D Gaussian representations and operates solely on RGB inputs. Whi…

cs.CV2024

EGSRAL: An Enhanced 3D Gaussian Splatting based Renderer with Automated Labeling for Large-Scale Driving Scene

Yixiong Huo, Guangfeng Jiang, Hongyang Wei +9

3D Gaussian Splatting (3D GS) has gained popularity due to its faster rendering speed and high-quality novel view synthesis. Some researchers have explored using 3D GS for reconstr…