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Data Generation Scheme for Thermal Modality with Edge-Guided Adversarial Conditional Diffusion Model

7 Aug 2024arXiv:2408.03748archive 2025-07-28

Guoqing Zhu, Honghu Pan, Qiang Wang, Chao Tian, Chao Yang, Zhenyu He

In challenging low light and adverse weather conditions,thermal vision algorithms,especially object detection,have exhibited remarkable potential,contrasting with the frequent struggles encountered by visible vision algorithms. Nevertheless,the efficacy of thermal vision algorithms driven by deep learning models remains constrained by the paucity of available training data samples. To this end,this paper introduces a novel approach termed the edge guided conditional diffusion model. This framework aims to produce meticulously aligned pseudo thermal images at the pixel level,leveraging edge information extracted from visible images. By utilizing edges as contextual cues from the visible domain,the diffusion model achieves meticulous control over the delineation of objects within the generated images. To alleviate the impacts of those visible-specific edge information that should not appear in the thermal domain,a two-stage modality adversarial training strategy is proposed to filter them out from the generated images by differentiating the visible and thermal modality. Extensive experiments on LLVIP demonstrate ECDM s superiority over existing state-of-the-art approaches in terms of image generation quality.

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Syntology Ran 15 of 16 code samples harvested from 1 repository linked to this paper; 1 has no recorded run. Of those that ran: 2 ran · honoured contract; 3 ran · violated contract; 4 ran · our draft was wrong; 2 ran · fixture could not drive it; 4 ran with no contract checked.

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2ran · honoured contract
3ran · violated contract
4ran · our draft was wrong
2ran · fixture could not drive it
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Normalize lengmo1996/ECDM/ecdm/modules/diffusionmodules/simple_unet.py official repository ran · our draft was wrong no licence file found · pointer only · c3a6b977022957cb · report
contour_extraction lengmo1996/ECDM/ecdm/models/diffusion/ecdm_second_stage.py official repository ran fingerprinted no licence file found · pointer only · 9e47ade220c9b3ae · report
default lengmo1996/ECDM/ecdm/modules/attention.py official repository ran · violated contract no licence file found · pointer only · 424012cb37b31172 · report
disabled_train lengmo1996/ECDM/ecdm/models/diffusion/ddpm_condition.py official repository ran · violated contract no licence file found · pointer only · 4cb732f513d69dfd · report
exists lengmo1996/ECDM/ecdm/modules/attention.py official repository ran · violated contract no licence file found · pointer only · aa5486a3650902d8 · report
get_norm_layer lengmo1996/ECDM/ecdm/models/patchgan.py official repository ran no licence file found · pointer only · ca1185ad84a317c9 · report
get_timestep_embedding lengmo1996/ECDM/ecdm/modules/diffusionmodules/simple_unet.py official repository ran · fixture could not drive it fingerprinted no licence file found · pointer only · cb49209c125de1b4 · report
isimage lengmo1996/ECDM/ecdm/util.py official repository ran no licence file found · pointer only · b1368330cf0f5642 · report
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make_beta_schedule lengmo1996/ECDM/ecdm/modules/diffusionmodules/util.py official repository ran · honoured contract no licence file found · pointer only · 3bd7e0cdbd131fdb · report
make_ddim_sampling_parameters lengmo1996/ECDM/ecdm/modules/diffusionmodules/util.py official repository ran · fixture could not drive it no licence file found · pointer only · 3ee640131c9d4362 · report
make_ddim_timesteps lengmo1996/ECDM/ecdm/modules/diffusionmodules/util.py official repository ran · honoured contract no licence file found · pointer only · 0ea4e960ea54514c · report
nonlinearity lengmo1996/ECDM/ecdm/modules/diffusionmodules/simple_unet.py official repository ran · our draft was wrong fingerprinted no licence file found · pointer only · 3137073275f8c21a · report
uniform_on_device lengmo1996/ECDM/ecdm/models/diffusion/ddpm_condition.py official repository ran · our draft was wrong no licence file found · pointer only · d48d8354986e3b0e · report
uniq lengmo1996/ECDM/ecdm/modules/attention.py official repository ran · our draft was wrong no licence file found · pointer only · 9a299fe5ae09e407 · report
log_txt_as_img lengmo1996/ECDM/ecdm/util.py official repository unverified no licence file found · pointer only · f9bd2e83191afad1 · report

Tasks

Image GenerationObject Detectionobject-detection

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Methods

Diffusion

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