This photograph showcases a research poster presented at CVPR (Conference on Computer Vision and Pattern Recognition) 2024 in Seattle, Washington. The poster is titled "Zero-Reference Low-Light Enhancement" and is authored by Wenjing Wang, Huan Yang, and Jianlong Yang. It discusses a novel method for enhancing low-light images using a zero-reference approach, which learns solely from normal light images, thereby reducing the need for supervision.

**Introduction Section:**
- **Objective:** Improve the robustness of data usage during training, illumination-specific hyper-parameters, and unseen scenarios.
- **Methodology:** The researchers designed an illumination-invariant prior serving as a bridge between normal light and low-light images.

**Method Section:**
- The training framework includes predicting a physical quadruple prior and reconstructing the prior back to images using an encoder-decoder architecture.
- The solution to detail degradation involves bypassing the standard decoded method.

**Diagrams and Examples:**
- Illustrated tables show the process of training on normal light images and inferring on low-light images.
- Additional visual comparisons depict the effectiveness of their method in enhancing details in low-light conditions compared to images without specified components.

The poster is affixed to a black frame, with some attendees partially visible in the background, highlighting an engaging conference environment.
Text transcribed from the image:
CVPR
JUNE 17-21, 2024
SEATTLE, WA

Zero-Reference Low-Light Enhancement
Wenjing Wang1 Huan Yang2 Jianlong Yang2

Introduction

Zero-Reference Low-Light Enhancement: learn solely with normal light images, reducing the need for supervision

Our aim: improve the robustness to
- Data usage during training
- Illumination-specific hyper-parameters
- Unseen scenarios

Our methodology: design an illumination-invariant prior that serves as a bridge between normal light and low-light images

Training on normal light images
   Reconstruction Loss
 ┌───────┬───────┬───────────────┐
 │       │       │               │
 │       │       │               │
 │       │       │               │
 │       │       │               │
 │       │       │               │
├───────┼───────┼───────────────┤
│       │       │               │
│       │       │               │
│       │       │               │
│       │       │               │
│       │       │               │
└───────┴───────┴───────────────┘ 

 Normal     Physical      Prior-to-Img      Output
 Light      Quadruple     Framework
 Input      Prior  

Illumination Invariant Features

Inference on low-light images
 ┌───────┬───────┬───────────────┐
 │       │       │               │
 │       │       │               │
 │       │       │               │
 │       │       │               │
 │       │       │               │
├───────┼───────┼───────────────┤
│       │       │               │
│       │       │               │
│       │       │               │
│       │       │               │
│       │       │               │
└───────┴───────┴───────────────┘ 

 Low-light  Physical      Prior-to-Img      Output
  Input     Quadruple     Framework
            Prior

Method

Training framework
- Predict a physical quadruple prior
- Reconstruct the prior back to image

─── SD Encoder

Solution of detail degradation: bypass
       ┌──────────────────────────────────────────────────────────────────────────┐
       │                                                                          │
       │     ┌───────────────┬───────────────┬───────────────┬───────────────┐    │
       │     │               │               │               │               │    │
       │     │               │               │               │               │    │
       │     │               │               │               │               │    │
       │     │               │               │               │               │    │
       │     └───────────────┴───────────────┴───────────────┴───────────────┘    │
       │                                                                          │
       │ ┌───────────┬───────────────┬───────────────┬───────────────┬────────┐  │
       │ │           │               │               │               │        │  │
       │ │           │               │               │               │        │  │
       │ │           │               │               │               │        │  │
       │ │           │               │               │               │        │  │
       │ └───────────┴───────────────┴───────────────┴───────────────┴────────┘  │
       │                                                                          │
       └──────────────────────────────────────────────────────────────────────────┘
         w/o H         w/o C
Low-light enhancement effects for different