3 citations · 3 across the 12 of their papers we have counts for
13 papers · 1 filter
Principled Reflection Separation via Nonlinear Superposition and Feature Interaction
Qiming Hu, Mingjia Li, Yuntong Li +1
Single-image reflection separation is fundamentally challenged by the entanglement of transmission and reflection layers under complex image formation processes. Existing approache…
Internally Referenced Low-Light Enhancement
Peiyuan He, Hainuo Wang, Hengxing Liu +2
Self-supervised low-light image enhancement (LLIE) is highly appealing as it eliminates the reliance on external paired data. However, the lack of external references causes networ…
Representative Attention For Vision Transformers
Yuntong Li, Hainuo Wang, Hengxing Liu +2
Linear attention has emerged as a promising direction for scaling Vision Transformers beyond the quadratic cost of dense self-attention. A prevalent strategy is to compress spatial…
On the Global Photometric Alignment for Low-Level Vision
Mingjia Li, Tianle Du, Hainuo Wang +2
Supervised low-level vision models rely on pixel-wise losses against paired references, yet paired training sets exhibit per-pair photometric inconsistency, say, different image pa…
Anchor then Polish for Low-light Enhancement
Tianle Du, Mingjia Li, Hainuo Wang +1
Low-light image enhancement is challenging due to entangled degradations, mainly including poor illumination, color shifts, and texture interference. Existing methods often rely on…
WiT: Waypoint Diffusion Transformers for Alleviating Trajectory Conflict in Pixel-Space Image Generation
Hainuo Wang, Mingjia Li, Xiaojie Guo
While recent Flow Matching models avoid the reconstruction bottlenecks of latent autoencoders by operating directly in pixel space, the raw pixel manifold provides little explicit…