Lihua Liu

Yuzhen Li, Zehang Deng, Yuxin Cao et al.

Previous works have shown that reducing parameter overhead and computations for transformer-based single image super-resolution (SISR) models (e.g., SwinIR) usually leads to a reduction of performance. In this paper, we present GRFormer, an efficient and lightweight method, which not only reduces the parameter overhead and computations, but also greatly improves performance. The core of GRFormer is Grouped Residual Self-Attention (GRSA), which is specifically oriented towards two fundamental components. Firstly, it introduces a novel grouped residual layer (GRL) to replace the Query, Key, Value (QKV) linear layer in self-attention, aimed at efficiently reducing parameter overhead, computations, and performance loss at the same time. Secondly, it integrates a compact Exponential-Space Relative Position Bias (ES-RPB) as a substitute for the original relative position bias to improve the ability to represent position information while further minimizing the parameter count. Extensive experimental results demonstrate that GRFormer outperforms state-of-the-art transformer-based methods for $\times$2, $\times$3 and $\times$4 SISR tasks, notably outperforming SOTA by a maximum PSNR of 0.23dB when trained on the DIV2K dataset, while reducing the number of parameter and MACs by about \textbf{60\%} and \textbf{49\% } in only self-attention module respectively. We hope that our simple and effective method that can easily applied to SR models based on window-division self-attention can serve as a useful tool for further research in image super-resolution. The code is available at \url{https://github.com/sisrformer/GRFormer}.

Jiehong Lin, Lihua Liu, Dekun Lu et al.

Zero-shot 6D object pose estimation involves the detection of novel objects with their 6D poses in cluttered scenes, presenting significant challenges for model generalizability. Fortunately, the recent Segment Anything Model (SAM) has showcased remarkable zero-shot transfer performance, which provides a promising solution to tackle this task. Motivated by this, we introduce SAM-6D, a novel framework designed to realize the task through two steps, including instance segmentation and pose estimation. Given the target objects, SAM-6D employs two dedicated sub-networks, namely Instance Segmentation Model (ISM) and Pose Estimation Model (PEM), to perform these steps on cluttered RGB-D images. ISM takes SAM as an advanced starting point to generate all possible object proposals and selectively preserves valid ones through meticulously crafted object matching scores in terms of semantics, appearance and geometry. By treating pose estimation as a partial-to-partial point matching problem, PEM performs a two-stage point matching process featuring a novel design of background tokens to construct dense 3D-3D correspondence, ultimately yielding the pose estimates. Without bells and whistles, SAM-6D outperforms the existing methods on the seven core datasets of the BOP Benchmark for both instance segmentation and pose estimation of novel objects.

Lihua Liu, Jiehong Lin, Zhenxin Liu et al.

RGB-based novel object pose estimation is critical for rapid deployment in robotic applications, yet zero-shot generalization remains a key challenge. In this paper, we introduce PicoPose, a novel framework designed to tackle this task using a three-stage pixel-to-pixel correspondence learning process. Firstly, PicoPose matches features from the RGB observation with those from rendered object templates, identifying the best-matched template and establishing coarse correspondences. Secondly, PicoPose smooths the correspondences by globally regressing a 2D affine transformation, including in-plane rotation, scale, and 2D translation, from the coarse correspondence map. Thirdly, PicoPose applies the affine transformation to the feature map of the best-matched template and learns correspondence offsets within local regions to achieve fine-grained correspondences. By progressively refining the correspondences, PicoPose significantly improves the accuracy of object poses computed via PnP/RANSAC. PicoPose achieves state-of-the-art performance on the seven core datasets of the BOP benchmark, demonstrating exceptional generalization to novel objects. Code and trained models are available at https://github.com/foollh/PicoPose.

Zhengjun Cao, Lihua Liu

In 2012, Groth, et al. [J. ACM, 59 (3), 1-35, 2012] developed some new techniques for noninteractive zero-knowledge (NIZK) and presented: the first perfect NIZK argument system for all NP; the first universally composable NIZK argument for all NP in the presence of an adaptive adversary; the first noninteractive zap for all NP, which is based on a standard cryptographic security assumption. These solved several long-standing open questions. In this note, we remark that their basic system is flawed because the prover can cheat the verifier to accept a false claim. Thus, these problems remain open now.

Zhengjun Cao, Lihua Liu

We show that the Lei et al.'s scheme [Information Sciences, 280 (2014), 205-217] fails, because the verifying equation does not hold over the infinite field R. For the field R, the computational errors should be considered seriously. We also remark that the incurred communication cost in the scheme could be overtake the computational gain, which makes it somewhat artificial.

Zhengjun Cao, Lihua Liu

Recently, Lu et al. have proposed two image search schemes based on additive homomorphic encryption [IEEE Access, 2 (2014), 125-141]. We remark that both two schemes are flawed because: (1) the first scheme does not make use of the additive homomorphic property at all; (2) the additive homomorphic encryption in the second scheme is unnecessary and can be replaced by a more efficient symmetric key encryption.

Lihua Liu, Zhengjun Cao

We show that the verifying equations in the scheme [Theoretical Computer Science, 562 (2015), 112-121] cannot filter out some malformed values returned by the malicious servers. We also remark that the two untrusted programs model adopted in the scheme is somewhat artificial, and discuss some reasonable scenarios for outsourcing computations.

Zhengjun Cao, Lihua Liu

Recently, Wang et al. [IEEE INFOCOM 2011, 820-828], and Nie et al. [IEEE AINA 2014, 591-596] have proposed two schemes for secure outsourcing of large-scale linear programming (LP). They did not consider the standard form: minimize c^{T}x, subject to Ax=b, x>0. Instead, they studied a peculiar form: minimize c^{T}x, subject to Ax = b, Bx>0, where B is a non-singular matrix. In this note, we stress that the proposed peculiar form is unsolvable and meaningless. The two schemes have confused the functional inequality constraints Bx>0 with the nonnegativity constraints x>0 in the linear programming model. But the condition x>0 is indispensable to the simplex method. Therefore, both two schemes failed.

Zhengjun Cao, Lihua Liu

At Eurocrypt'99, Paillier presented a public-key cryptosystem based on a novel computational problem. It has interested many researchers because it was additively homomorphic. In this paper, we show that there is a big difference between the original Paillier's encryption and some variants. The Paillier's encryption can be naturally transformed into a signature scheme but these variants miss the feature. In particular, we simplify the alternative decryption procedure of Bresson-Catalano-Pointcheval encryption scheme proposed at Asiacrypt'03. The new version is more applicable to cloud computing because of its double trapdoor decryption mechanism and its flexibility to be integrated into other cryptographic schemes. It captures a new feature that its two groups of secret keys can be distributed to different users so as to enhance the robustness of key management.

Zhengjun Cao, Lihua Liu

Fully homomorphic encryption (FHE) allows anyone to perform computations on encrypted data, despite not having the secret decryption key. Since the Gentry's work in 2009, the primitive has interested many researchers. In this paper, we stress that any computations performed on encrypted data are constrained to the encrypted domain (finite fields or rings). This restriction makes the primitive useless for most computations involving common arithmetic expressions and relational expressions. It is only applicable to the computations related to modular arithmetic. We want to reaffirm that cryptography uses modular arithmetic a lot in order to obscure and dissipate the redundancies in a plaintext message, not to perform any numerical calculations. We think it might be an overstated claim that FHE is of great importance to client-server computing or cloud computing.

Zhengjun Cao, Lihua Liu

Key establishment is any process whereby a shared secret key becomes available to two or more parties, for subsequent cryptographic use such as symmetric-key encryption. Though it is widely known that the primitive of encryption is different from key establishment, we find some researchers have confused the two primitives. In this note, we shall clarify the fundamental difference between the two primitives, and point out that the Boneh-Gentry-Waters broadcast encryption scheme and its like are key establishment schemes, not encryption schemes.

Zhengjun Cao, Lihua Liu

The primitive of private broadcast encryption introduced by Barth, Boneh and Waters, is used to encrypt a message to several recipients while hiding the identities of the recipients. In their construction, a recipient has to first decrypt the received ciphertext to extract the verification key for one-time signature. He then uses the verification key to check whether the ciphertext is malformed. The authors did not consider that information delivered over a channel, especially over a broadcast channel, should be authenticated as to its origin. We remark that the conventional public key signature suffices to authenticate data origin and filter out all malformed ciphertexts. We also discuss the disadvantages of the primitive of one-time signature used in their construction.

Zhengjun Cao, Lihua Liu

Attribute-based encryption (ABE) which allows users to encrypt and decrypt messages based on user attributes is a type of one-to-many encryption. Unlike the conventional one-to-one encryption which has no intention to exclude any partners of the intended receiver from obtaining the plaintext, an ABE system tries to exclude some unintended recipients from obtaining the plaintext whether they are partners of some intended recipients. We remark that this requirement for ABE is very hard to meet. An ABE system cannot truly exclude some unintended recipients from decryption because some users can exchange their decryption keys in order to maximize their own interests. The flaw discounts the importance of the cryptographic primitive.

Zhengjun Cao, Lihua Liu

We remark that the Bellare-Rivest protocol for translucent cryptography [J. Cryptology (1999) 12: 117-139] can not truly enable the government to decrypt partial encrypted communications.