Blind detection of the forged regions in digital images is an effective
authentication means to counter the malicious use of local image editing
techniques. Existing encoder-decoder forensic networks overlook the fact that
detecting complex and subtle tampered regions typically requires more feedback
information. In this paper, we propose a Progressive FeedbACk-enhanced
Transformer (ProFact) network to achieve coarse-to-fine image forgery
localization. Specifically, the coarse localization map generated by an initial
branch network is adaptively fed back to the early transformer encoder layers
for enhancing the representation of positive features while suppressing
interference factors. The cascaded transformer network, combined with a
contextual spatial pyramid module, is designed to refine discriminative
forensic features for improving the forgery localization accuracy and
reliability. Furthermore, we present an effective strategy to automatically
generate large-scale forged image samples close to real-world forensic
scenarios, especially in realistic and coherent processing. Leveraging on such
samples, a progressive and cost-effective two-stage training protocol is
applied to the ProFact network. The extensive experimental results on nine
public forensic datasets show that our proposed localizer greatly outperforms
the state-of-the-art on the generalization ability and robustness of image
forgery localization. Code will be publicly available at
this https URL

我们提出了一种 Progressive FeedbACk-enhanced Transformer (ProFact) 网络，用于实现粗细图像伪造定位。该网络通过自适应反馈，将初步分支网络生成的粗定位图传递给早期 Transformer 编码层，以增强正特征的表达并抑制干扰因素。结合上下文空间金字塔模块的级联变压器网络用于改进鉴别式法庭特征，提高伪造定位的准确性和可靠性。实验结果表明，我们提出的定位器在图像伪造定位的泛化能力和稳健性方面远远超过现有技术。

渐进反馈增强转换器用于图像篡改定位

Progressive Feedback-Enhanced Transformer for Image Forgery Localization

In blind detection, a set of candidates has to be decoded within a strict
time constraint, to identify which transmissions are directed at the user
equipment. Blind detection is required by the 3GPP LTE/LTE-Advanced standard,
and it will be required in the 5th generation wireless communication standard
(5G) as well. Polar codes have been selected for use in 5G: thus, the issue of
blind detection of polar codes must be addressed. We propose a polar code blind
detection scheme where the user ID is transmitted instead of some of the frozen
bits. A first, coarse decoding phase helps selecting a subset of candidates
that is decoded by a more powerful algorithm: an early stopping criterion is
also introduced for the second decoding phase. Simulations results show good
missed detection and false alarm rates, along with substantial latency gains
thanks to early stopping. We then propose an architecture to implement the
devised blind detection scheme, based on a tunable decoder that can be used for
both phases. The architecture is synthesized and implementation results are
reported for various system parameters. The reported area occupation and
latency, obtained in 65 nm CMOS technology, are able to meet 5G requirements,
and are guaranteed to meet them with even less resource usage in the latest
technology nodes.

本文提出一种针对极化码的盲检测方案，其中用户 ID 被传输替代了某些已冻结的比特。第一阶段的粗略解码可以帮助选择一个更小的子集，然后使用更强大的算法进行解码。通过引入早停准则，实现少量系统资源的同时，实现了低的漏检率和误警率以及显著的延迟优势，该方案的架构是基于可以用于两个阶段的可调解码器。

极化码盲检测方案的设计和实现

Design and Implementation of a Polar Codes Blind Detection Scheme

In blind detection, a set of candidates has to be decoded within a strict
time constraint, to identify which transmissions are directed at the user
equipment. Blind detection is an operation required by the 3GPP
LTE/LTE-Advanced standard, and it will be required in the 5th generation
wireless communication standard (5G) as well. We propose a blind detection
scheme based on polar codes, where the radio network temporary identifier
(RNTI) is transmitted instead of some of the frozen bits. A low-complexity
decoding stage decodes all candidates, selecting a subset that is decoded by a
high-performance algorithm. Simulations results show good missed detection and
false alarm rates, that meet the system specifications. We also propose an
early stopping criterion for the second decoding stage that can reduce the
number of operations performed, improving both average latency and energy
consumption. The detection speed is analyzed and different system parameter
combinations are shown to meet the stringent timing requirements, leading to
various implementation trade-offs.

提出了一种基于极化码的盲检测方案，通过在数据流中传输固定位替代通信标识符（RNTI），显著降低了解码过程的复杂度，并且运用早停策略可以进一步提升检测速度和降低能耗，并且通过对不同系统参数的调整，满足了严格的时间要求。