Perceived photorealism in architectural 3D rendering is not determined solely by physical accuracy or rendering complexity but also by a limited set of visual cues that observers rely on when judging realism. This literature review synthesizes findings from 41 peer-reviewed studies spanning perception science, computer graphics, and immersive visualization, with the aim of identifying the cues that most strongly contribute to perceived photorealism in rendered scenes. Convergent evidence from psychophysical experiments, user studies in virtual and augmented reality, and rendering-oriented analyses indicate that six cue categories consistently dominate realism judgments. Across the reviewed literature, realism judgments depend less on scene complexity or the number of visual elements and more on the consistency and plausibility of these cues for supporting inferences about shape, material, and spatial layout. These findings suggest that photorealism emerges from the alignment of the rendered image structure with perceptual expectations learned from real-world visual experience. The implications for architectural visualization workflows and directions for future research on cue interactions and perceptual thresholds are discussed.

Procedural textures trade image storage for runtime shader evaluation, whereas baked bitmaps replace repeated procedural computation with stored image data. Controlled path-tracing comparisons that isolate this representation choice remain limited. This study compares four procedural Base Color graphs with their ${2048}^2$ baked bitmap counterparts in Blender Cycles 5.2 on a GIGABYTE NVIDIA GTX 1050 Ti (GIGA-BYTE Technology Co., Ltd., New Taipei City, Taiwan) while holding geometry, lighting, camera, sampling and BSDF parameters constant. Three texture graphs—checker, noise and multifractal—were examined in a predefined ordering by computational demand, while ambient occlusion was analyzed separately as a ray-traced effect. The primary experiment comprised 480 renders, of which 360 were analyzed using block means as the inferential unit. Block-level models showed that the procedural checker was 0.65% faster than its baked counterpart, whereas the bitmap representation was 1.73% faster for noise and 3.53% faster for multifractal; all four primary representation effects had 95% confidence intervals excluding zero after Holm adjustment. Baking ambient occlusion reduced render time by 67.74% under the tested configuration. The bitmap branch increased Cycles-reported internal peak memory by exactly 16 MiB at ${2048}^2$, while resolution tests produced increments of 1, 4 and 64 MiB at ${512}^2$, ${1024}^2$ and ${4096}^2$, respectively. Because the ${2048}^2$ baked multifractal showed lower visual agreement with its procedural source, a targeted ${4096}^2$ follow-up comprising a further 120 renders, of which 90 were analyzed, was conducted. Increasing the multifractal bake resolution improved SSIM from 0.886 to 0.936, increased the image-texture footprint from 16 to 64 MiB, and reduced the bitmap render-time advantage from 3.53% to 1.73%. Across the three primary texture graphs, the bitmap advantage increased along the predefined ordering by computational demand; however, computational demand was not isolated from differences in algorithm, coordinate system, and spatial structure. The results therefore demonstrate configuration-specific trade-offs among render time, image-memory footprint, and representation fidelity rather than a universal preference for either representation.

This systematic review examined the use and perceptual validation of four full-reference image quality metrics—HDR-VDP-2, LPIPS, DISTS, and SSIM—in computer-generated and rendered imagery. Among 283 included studies, SSIM was reported in 228 (80.6%) and LPIPS in 147 (51.9%), whereas HDR-VDP-2 and DISTS appeared in four each (1.4%). Only 23 studies (8.1%) included relevant human or subjective evaluation, and 13 (4.6%) directly tested metric–human agreement. Neural rendering, novel-view synthesis, and 3D reconstruction accounted for 175 studies (61.8%). Metric–human agreement varied with content, artifact type, alignment, viewing conditions, and perceptual task, while cue-specific evidence was uneven. The review therefore identifies a clear gap between metric adoption and perceptual validation. Metric selection should be matched to the rendering attribute, reference image, viewing conditions, and perceptual question.