Is this you? Claim this profile to correct it, add a bio and choose the work people see first.
Claim this profileWorks99 from public data
- Seedream 4.0: Toward Next-generation Multimodal Image Generation253
This work introduces Seedream 4.0, an efficient and high-performance multimodal image generation system that unifies text-to-image (T2I) synthesis, image editing, and multi-image composition within a single framework, and develops a highly efficient diffusion transformer with a powerful VAE which allows for efficient training of the model.
- VmambaIR: Visual State Space Model for Image Restoration242
The proposed VmambaIR is one of the first works to introduce State Space Models (SSMs) with linear complexity into comprehensive image restoration tasks, and highlights the potential of state space models as promising alternatives to the transformer and CNN architectures in serving as foundational frameworks for next-generation low-level visual tasks.
- Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learning240
A controllable text-to-video (T2V) diffusion model, called Control-A-Video, capable of maintaining consistency while customizable video synthesis, based on a pre-trained conditional text-to-image (T2I) diffusion model.
- Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios235
Extensive experiments show that Next-ViT significantly outperforms existing CNNs, ViTs and CNN-Transformer hybrid architectures with respect to the latency/accuracy trade-off across various vision tasks.
- Building fast and compact convolutional neural networks for offline handwritten Chinese character recognition165
A nine-layer CNN for HCCR consisting of 3755 classes is designed, and an algorithm is devised that can reduce the networks computational cost by nine times and compress the network to 1/18 of the original size of the baseline model, with only a 0.21% drop in accuracy.
- FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation156
FreeSeg is proposed, a generic framework to accomplish Unified, Universal and Open-Vocabulary Image Segmentation, which optimizes an all-in-one network via one-shot training and employs the same architecture and parameters to handle diverse segmentation tasks seamlessly in the inference procedure.
- Diffusion Adversarial Post-Training for One-Step Video Generation153
This work proposes Adversarial Post-Training (APT) against real data following diffusion pre-training for one-step video generation, and introduces several improvements to the model architecture and training procedures, along with an approximated R1 regularization objective.
- Seedream 3.0 Technical Report150
Overall capabilities of Seedream 3.0 are enhanced, in particular for text-rendering in complicated Chinese characters which is important to professional typography generation, and it provides native high-resolution output, allowing it to generate images with high visual quality.
- 149
- Activation Modulation and Recalibration Scheme for Weakly Supervised Semantic Segmentation146
A novel activation modulation and recalibration scheme that establishes a new state-of-the-art performance on the PASCAL VOC 2012 dataset, surpassing not only current methods trained with the image-level of supervision but also some methods relying on stronger supervision, such as saliency label.
- AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration94
This work designs a unified search space that consists of all possible time steps and various architectures and introduces a two stage evolutionary algorithm to find the optimal solution in the designed search space.
- Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model90
This technical report presents a cost-efficient strategy for training a video generation foundation model called Seaweed-7B trained from scratch using 665,000 H100 GPU hours and highlights the key design decisions that enhance the performance of the medium-sized diffusion model.
- 81
- Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model73
This work introduces an acceleration framework that boosts inference speed by over 10X and distinguishes itself through precise multilingual and dialect lip-syncing, dynamic cinematic camera control, and enhanced narrative coherence, positioning it as a robust engine for professional-grade content creation.
- Heavy metal removal from aqueous solutions by chitosan-based magnetic composite flocculants73
Characterization results show that the three magnetic carboxymethyl chitosan-based flocculant have been successfully prepared with good magnetic induction properties and shows excellent flocculation performance in removing soluble heavy metals.
- AffineQuant: Affine Transformation Quantization for Large Language Models72
This paper advocates for the direct optimization using equivalent Affine transformations in PTQ (AffineQuant) using the corresponding inverse matrix to ensure equivalence between the pre- and post-quantization outputs of PTQ, thereby maintaining its efficiency and generalization capabilities.
- Thermosensitive in situ nanogel as ophthalmic delivery system of curcumin: development, characterization, in vitro permeation and in vivo pharmacokinetic studies71
Results demonstrated that CUR-CNLC-GEL could become a potential formulation for increasing the bioavailability of CUR in the aqueous humor by enhancing corneal permeation and retention capacity.
- Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model67
This work presents Seedream 2.0, a native Chinese-English bilingual image generation foundation model that excels across diverse dimensions, which adeptly manages text prompt in both Chinese and English, supporting bilingual image generation and text rendering.
- 67
- 61
- Flocculation of combined contaminants of dye and heavy metal by nano-chitosan flocculants60
It is proved that nanoflocculants made by modifying CMCTS with different structures can demonstrate ideal flocculation removal performance for dye and heavy metal wastewaters.
- 60
- SepViT: Separable Vision Transformer55
The novel window token embedding and grouped self-attention are employed to compute the attention relationship among windows with negligible cost and establish long-range visual interactions across multiple windows, respectively.
- 54
- Online Multi-Granularity Distillation for GAN Compression54
This work proposes a novel online multi-granularity distillation (OMGD) scheme to obtain lightweight GANs, which contributes to generating highfidelity images with low computational demands and reveals that OMGD provides a feasible solution for the deployment of real-time image translation on resource-constrained devices.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
Report an error
Wrong papers, two people merged into one, or a profile that should not be here? Tell us and we will fix or hide it.