Computer Vision

AnyFit: Controllable virtual try-on for any attire combination across any scenario, exceeding existing methods in accuracy and scalability.

Animate3D animates any 3D model using multi-view video diffusion, achieving superior spatiotemporal consistency and straightforward mesh animation.

Image generation gets a speed boost with TiTok, a novel 1D image tokenizer that uses just 32 tokens for high-quality image reconstruction and generation, achieving up to 410x faster processing than st…

EMDiffusion trains clean diffusion models from corrupted data using an expectation-maximization algorithm, achieving state-of-the-art results on diverse imaging tasks.

RFPAR: A novel reinforcement learning-based attack enhances black-box pixel attacks by minimizing randomness and patch dependency, achieving state-of-the-art results in both image classification and o…

AlphaTablets revolutionizes 3D planar reconstruction from monocular videos with its novel rectangle-based representation featuring continuous surfaces and precise boundaries, achieving state-of-the-ar…

DiMR boosts image generation fidelity by cleverly combining multi-resolution networks with time-dependent layer normalization in diffusion models, achieving state-of-the-art results on ImageNet.

Multi-Path Aggregation (MPA) achieves comparable performance to state-of-the-art methods in multi-task image coding, by unifying feature representations with a novel all-in-one architecture and a two-…

Diffusion-KTO: Aligning text-to-image models with human preferences using simple likes/dislikes, maximizing expected human utility.

AirSketch generates aesthetically pleasing sketches directly from noisy hand-motion tracking data using a self-supervised controllable diffusion model, eliminating the need for expensive AR/VR equipme…

AID, a novel training-free method, significantly improves image interpolation by fusing inner/outer interpolated attention layers and using beta-distribution for coefficient selection, enhancing consi…

Accelerate Schrödinger Bridge Matching with Discrete-time IMF using only a few steps, achieving comparable results to existing hundred-step methods via D-GAN implementation.

SaSPA, a novel data augmentation method, boosts fine-grained visual classification accuracy by generating diverse, class-consistent synthetic images using structural and subject-preserving techniques.

AdvAD: A non-parametric diffusion process crafts imperceptible adversarial examples by subtly guiding an initial noise towards a target distribution, achieving high attack success rates with minimal p…

AdjointDEIS: Efficient gradients for diffusion models via bespoke ODE solvers, simplifying backpropagation and improving guided generation.

AdaptiveISP uses reinforcement learning to create a scene-adaptive ISP pipeline that dynamically optimizes for object detection, surpassing existing methods in accuracy and efficiency.

AIRS framework, guided by Evidential Q-learning, dynamically balances exploration and exploitation to achieve superior dense object detection accuracy by adaptively selecting important regions.

Adaptive Domain Learning (ADL) efficiently trains a cross-domain RAW image denoising model using limited target data and existing source data by intelligently discarding harmful source data and levera…

FG-DMs revolutionize image synthesis by jointly modeling image and condition distributions, achieving higher object recall and enabling flexible editing.

AdaPKC upgrades PeakConv for superior radar semantic segmentation by dynamically adjusting its receptive field, outperforming current state-of-the-art methods.