9 accepted papers
With the rapid advancement of deepfake technology, malicious face manipulations pose a significant threat to personal privacy and social security. However, existing proactive forensics methods typically treat deepfake detection, tampering localization, and source tracing as independent tasks, lackin
Deep learning-based image manipulation localization (IML) methods have achieved remarkable performance in recent years, but typically rely on large-scale pixel-level annotated datasets. To address the challenge of acquiring high-quality annotations, some recent weakly supervised methods utilize imag
Image manipulation localization (IML) faces a fundamental trade-off between minimizing annotation cost and achieving fine-grained localization accuracy. Existing fully-supervised IML methods depend heavily on dense pixel-level mask annotations, which limits scalability to large datasets or real-wor
While multi-task learning based automatic radiology report generation (RRG) is widely adopted to ensure clinical consistency, most focus on architectural designs yet remain limited to coarse linear scalarization strategies. These strategies can not effectively balance the hard constraints of discrim…
With the rapid evolution of deepfake technologies and the wide dissemination of digital media, personal privacy is facing increasingly serious security threats. Deepfake proactive forensics, which involves embedding imperceptible watermarks to enable reliable source tracking, serves as a crucial def
The denoising diffusion probabilistic model (DDPM) for image inpainting transforms the input image to Gaussian noise by adding noise in the forward process, and reconstitution masked regions that are consistent with unmasked regions from pure noise in the reverse process. Recently, on inpainting met…
Recently, the image super-resolution (SR) has made remarkable progress. However, due to the proliferation of resource-constrained scenarios, the computational-intensive SR technology is limited in portable devices. Therefore, high efficiency and lightweight become the key factors of image SR in the…
Recently, Transformer-based methods have gained popularity in skeleton-based action recognition due to their advantages in modeling long-range dependencies. However, Transformer lacks the inductive biases towards skeletal topology and tends to capture salient features, potentially overlooking subtle…
In recent years, it has been found that "grandmother cells" in the primary visual cortex (V1) of macaques can directly recognize visual input with complex shapes. This inspires us to examine the value of these cells in promoting the research of medical image segmentation. In this paper, we design a…