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Found 6 papers, 1 papers with code
$\text{R}^2$-Bench: Benchmarking the Robustness of Referring Perception Models under Perturbations
Referring perception, which aims at grounding visual objects with multimodal referring guidance, is essential for bridging the gap between humans, who provide instructions, and the environment where intelligent systems perceive.
Exploring Transferability for Randomized Smoothing
However, the model robustness, which is a critical aspect for safety, is often optimized for each specific task rather than at the pretraining stage.
ART$\boldsymbol{\cdot}$V: Auto-Regressive Text-to-Video Generation with Diffusion Models
Second, it preserves the high-fidelity generation ability of the pre-trained image diffusion models by making only minimal network modifications.
MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation
We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation.
Weakly-supervised Pre-training for 3D Human Pose Estimation via Perspective Knowledge
Based on MCPC, we propose a weakly-supervised pre-training (WSP) strategy to distinguish the depth relationship between two points in an image.
Learn to Scale: Generating Multipolar Normalized Density Maps for Crowd Counting
Dense crowd counting aims to predict thousands of human instances from an image, by calculating integrals of a density map over image pixels.
