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20212025
most citedGMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models

62 citations · 69 across the 5 of their papers we have counts for

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8 papers · 1 filter

cs.CV2025

DIFFVSGG: Diffusion-Driven Online Video Scene Graph Generation

Mu Chen, Liulei Li, Wenguan Wang +1

Top-leading solutions for Video Scene Graph Generation (VSGG) typically adopt an offline pipeline. Though demonstrating promising performance, they remain unable to handle real-tim…

cs.CV2024

Human-Object Interaction Detection Collaborated with Large Relation-driven Diffusion Models

Liulei Li, Wenguan Wang, Yi Yang

Prevalent human-object interaction (HOI) detection approaches typically leverage large-scale visual-linguistic models to help recognize events involving humans and objects. Though…

cs.CV2024

Vision-Language Navigation with Energy-Based Policy

Rui Liu, Wenguan Wang, Yi Yang

Vision-language navigation (VLN) requires an agent to execute actions following human instructions. Existing VLN models are optimized through expert demonstrations by supervised be…

cs.CV2024

Hydra-SGG: Hybrid Relation Assignment for One-stage Scene Graph Generation

Minghan Chen, Guikun Chen, Wenguan Wang +1

DETR introduces a simplified one-stage framework for scene graph generation (SGG) but faces challenges of sparse supervision and false negative samples. The former occurs because e…

cs.CV202262 cited

GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models

Chen Liang, Wenguan Wang, Jiaxu Miao +1

Prevalent semantic segmentation solutions are, in essence, a dense discriminative classifier of p(class|pixel feature). Though straightforward, this de facto paradigm neglects the…

cs.CV20222 cited

Locality-Aware Inter-and Intra-Video Reconstruction for Self-Supervised Correspondence Learning

Liulei Li, Tianfei Zhou, Wenguan Wang +3

Our target is to learn visual correspondence from unlabeled videos. We develop LIIR, a locality-aware inter-and intra-video reconstruction framework that fills in three missing pie…